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Volume 5 Issue 4 (October 2014)

ISSN 2228-9860 eISSN 1906-9642

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In This Issue Differential Effects of Sucrose and Plant Growth Regulator on Shoot Multiplication and Bulbil Formation in Oxalis Versicolour In Vitro

Preparation of Activated Carbon from Sindora Siamensis Seed and Canarium Sublatum Guillaumin fruit for Methylene Blue Adsorption

Use of Filter Media Made from Vetiver Grass Root Ash for Water Treatment

A Review of Resource-Constrained Project Scheduling Problems (RCPSP) Approaches and Solutions

Comparison between Analytical Results and Response of the Laboratory-Scaled Truss Bridges under the Moving Car Load

Cover Photo is from Samarn Srisa-ard research article in this issue (Preparation of Activated Carbon from Sindora Siamensis Seed and Canarium Sublatum Guillaumin fruit for Methylene Blue Adsorption). The photo depicts SEM micrographs for (a) raw ash, (b) SSAC for activated at 500°C, (c) SSAC for activated at 600°C and (d) SSAC for activated at 700°C.

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International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies

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International Editorial Board Editor-in-Chief Ahmad Sanusi Hassan, PhD Associate Professor Universiti Sains Malaysia, MALAYSIA

Executive Editor Boonsap Witchayangkoon, PhD Associate Professor Thammasat University, THAILAND

Noble Editorial Board: Professor Dr.Mikio SATOMURA (Shizuoka University, JAPAN) Professor Dr.Chuen-Sheng Cheng (Yuan Ze University, TAIWAN) Professor Dr.I Nyoman Pujawan (Sepuluh Nopember Institute of Technology, INDONESIA) Professor Dr.Neven Duić (University of Zagreb, CROATIA) Professor Dr.Lee, Yong-Chang (Incheon City College SOUTH KOREA) Professor Dr.Dewan M. Nuruzzaman (Dhaka University of Engineering & Technology, BANGLADESH) Professor Dr. Lutero Carmo de Lima (State University of Ceará, BRAZIL )

Scientific and Technical Committee & Editorial Review Board on Engineering, Technologies and Applied Sciences: Associate Prof. Dr. Paulo Cesar Lima Segantine (University of São Paulo, BRASIL) Associate Prof. Dr. Kurt B. Wurm (New Mexico State University, USA ) Associate Prof. Dr. Truong Vu Bang Giang (Vietnam National University, Hanoi, VIETNAM ) Dr.H. Mustafa Palancıoğlu (Erciyes University, TURKEY) Associate Prof.Dr.Peter Kuntu-Mensah (Texas A&M University-Corpus Christi, USA) Associate Prof. Dr. Masato SAITOH (Saitama University, JAPAN ) Assistant Prof.Dr. Zoe D. Ziaka (International Hellenic University, GREECE ) Associate Prof.Dr. Junji SHIKATA (Yokohama National University, JAPAN) Assistant Prof.Dr. Akeel Noori Abdul Hameed (University of Sharjah, UAE) Assistant Prof.Dr. Rohit Srivastava (Indian Institute of Technology Bombay, INDIA) Madam Wan Mariah Wan Harun (Universiti Sains Malaysia, MALAYSIA ) Dr. David Kuria (Kimathi University College of Technology, KENYA ) Dr. Mazran bin Ismail (Universiti Sains Malaysia, MALAYSIA ) Dr. Salahaddin Yasin Baper (Salahaddin University - Hawler, IRAQ ) Dr. Foong Swee Yeok (Universiti Sains Malaysia, MALAYSIA)

2014 International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies.

i

:: International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies

Volume 5 Issue 4 (October, 2014) ISSN 2228-9860 http://TuEngr.com eISSN 1906-9642

FEATURE PEER-REVIEWED ARTICLES Differential Effects of Sucrose and Plant Growth

Regulator on Shoot Multiplication and Bulbil Formation in

Oxalis Versicolour In Vitro

227

Preparation of Activated Carbon from Sindora Siamensis

Seed and Canarium Sublatum Guillaumin fruit for

Methylene Blue Adsorption

235

Use of Filter Media Made from Vetiver Grass Root Ash for

Water Treatment 247

A Review of Resource-Constrained Project Scheduling

Problems (RCPSP) Approaches and Solutions 253

Comparison between Analytical Results and Response of

the Laboratory-Scaled Truss Bridges under the Moving

Car Load

287

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Differential Effects of Sucrose and Plant Growth Regulator on Shoot Multiplication and Bulbil Formation in Oxalis Versicolour In Vitro

Nattapong Chanchula a , Tassanai Jaruwattanaphan a , and Anchalee Jala b*

a Department of Horticulture, Faculty of Agriculture, Kasetsart University, Bangkhen, Bangkok,

THAILAND, 10220, THAILAND b Department of Biotechnology, Faculty of Science and Technology, Thammasat University, Rangsit Campus, Pathumthani, THAILAND, 12121, THAILAND A R T I C L E I N F O

A B S T RA C T

Article history: Received 24 March 2014 Received in revised form 04 June 2014 Accepted 16 June 2014 Available online 19 June 2014 Keywords: Bicolor Flower; Bulb; Tissue culture; NAA; BA.

Explants from young leaves and stem nodes of Oxalis versicolour were used and cultured on MS medium supplemented with different concentration of 2,4-D. The best result showed that cluster of callus were formed and proliferated around the base of explants on MS medium supplemented with 0.1 mg/l 2,4-D. Callus transferred to MS medium supplemented with various concentrations of NAA and BA. After nine weeks, callus regenerated to be new shoots. The highest average length of stolon was from MS medium supplemented with 0.1mg/l NAA and 0.1 mg/l BA and number of plantlets was from MS medium supplemented with 4.0 mg/l NAA and 5.0 mg/l BA. Plantlets were cultured on MS medium supplemented with different concentrations of sucrose for ten weeks. It was found that all parameters: number of plantlets, bulbil sized, length of stolon, and number of nodes were significant difference (p≤0.05). Number of flowers and sized of flowers found only in MS medium supplemented with 9–10 % of sucrose.

2014 INT TRANS J ENG MANAG SCI TECH.

1. Introduction Bicolored Oxalis Versicolor (Candy Cane Sorrel) is a unique bulb with really spectacular


*Corresponding author (Anchalee Jala). Tel/Fax: +66-2-5644440-59 Ext. 2450, E-mail addresses: [email protected]. 2014. International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies. Volume 5 No.4 ISSN 2228-9860 eISSN 1906-9642. Online available at http://tuengr.com/V05/0227.pdf.

227



flowers. Oxalis is belonging to Oxalidaceae. Their origin is in Americas and South Africa.

The toxic principle is soluble oxalate. This oxalis is very beautiful in full bloom. They are

even more stunning when they have not quite opened up completely and display a striking red

and white striped pattern. They can be planted in the garden or in a planter on the patio or

window-box. The foliage is three very narrow petals on each leaf and is not much like the

clover we are used to seeing. The bulbs are very tiny, about the size of a fingernail. The thin

plants will spring up in no time at all and are to produce many dainty 1/2" flowers and

watering once the soil has become dry, however, do not soak.

This plant propagated by growing bulb. Plant tissue culture is one choice that can

micropropagated and increase about 10000 plants within 2 months. Direct micropropagation

system through enhanced young leaves or axillary bud development and organogenesis has

been reported for different species of gladiolus (Jala, 2013). Various results have also been

reported for the role of cytokinins in plant regeneration from callus initiated from different

organs of Gladiolus such as young leaves and cormel slices (Kamo 1994). Since the callus

initiation and regeneration depend variously on cultivated varieties, explants and growth

regulators used in culture media (Kamo 1994, 1995), the present investigation was undertaken

to determine the proper concentrations of growth regulators for callus initiation and

regeneration of a locally cultivated, taking young leaves as explant.

2. Materials and Methods

2.1 Culture Establishment and Growth Oxalis plants were grown in green house. Young leaf and stem nodes were used as

explants. Explants were surface sterilized by soaking with 70% alcohol for 10 sec, followed

by 10%(v/v) Clorox (NaOCl) containing 15 drops/l Tween 20 for 10 min, 5% (v/v) Clorox

for 15 min and washed with sterilized distilled water 3 times for 5 min each, to remove the

Clorox. The ends of the explants were cut off in both sides and cultured on MS (Murashige

and Skoog, 1962). After 2 weeks, cleaned cultures were transferred to MS medium

supplemented with different combination of 2,4-D 2% sucrose, 0.25% gelrite at pH 5.7 and

autoclaving at 121o C for 20 min. The cultures were maintained at 25 ± 2° C under a 16-hour

photoperiod with illumination provided by cool fluorescent lamps at an intensity of 60

µmolm-2 sec-1 (TLD 36 w/853350 lm Phillips, Thailand). These cultures were maintained in a

228 Nattapong Chanchula, Tassanai Jaruwattanaphan, and Anchalee Jala

proliferating state by subculturing every 3 weeks into the same medium 4 times.

2.2 Multiplication Callus were cultured on MS medium supplemented with combination of (0.1, 1, 2, 3, 4

mg/l) NAA and (0.1, 1, 2, 3, 4, 5 mg/l) BA and various concentrations of ( 2,3,4,5,6,7,8,9,and

10 %) sucrose. These treatments were subcultured every 3 weeks for 4 times. Shoot

proliferation, bulb formation and their growth are displayed in Table 2 and 3.

3. Statistical Analysis Experiments were set up in Completely Randomized Design (CRD). Each treatment

consisted of 20 replicates for the first second and third experiment. The test of statistical

significance was done by applying DMRT at 1% and 5% confidence level using SAS

statistical software.

Table 1: Effect of 2,4-D on sized and color of callus after cultured for 8 weeks. 2,4-D conc. (mg/l) Sized of callus Color of callus

0.1 4.60 ± 0.45a Light green 1 1.64 ± 0.39b Light green 2 1.29 ± 0.32b Light green 3 1.76 ± 0.38b cream 5 1.68 ± 0.23b Cream

F-test ** - % C.V. 16.68 -

** Mean within the same column followed by the same alphabet were not significant difference using DMRT, p≤0.05.

Figure 1: Callus induction on MS medium supplemented with 2,4–D

A - 0.1 mg/l, B - 5.0 mg/l.

4. Results After 2 weeks, explants from the disinfestation process resulted in a survival rate about

75 %, These explants were cultured on MS medium supplemented with different

concentration of 2,4-D. After cultured for 4 weeks, callus were formed and proliferated

around the base of explants which attached to the medium. The sized of callus were

A B 1cm 1cm


229



significant differences (p≤0.05). Cluster of callus were formed with different sized and

depended on concentration of 2,4-D, as showed on Table 1 and Figure 1.

4.1 Result of Multiplication Callus transferred to MS medium supplemented with various concentrations of NAA and

BA. After cultured for 4 weeks, it was found that callus regenerated to be new shoots.

Average length of stolon and number of plantlets were depended on concentration of NAA

and BA in the MS medium and were highly significant difference (p≤0.01) (Table 2). The

result showed that MS medium supplemented with 0.4 mg/l NAA and 0.5 mg/l BA gave the

highest number of plantlets (71.6 plantlets). MS medium supplements with 0.1 mg/l NAA

and 0.1 mg/l BA gave the longest length of stolon (11.10cm).

Table 2: Effect of NAA and BA concentration on inducing length of stolon and number of plantlets after cultured for 9 weeks.

Plant growth regulator length of stolon (cm) Number of plantlets NAA (mg/l) BA(mg/l) 0 0 13.30a ± 4.62 1.10a ± 0.31

0.1 0.1 11.10a ± 2.80 4.10b ± 2.55

0.5 7.40b ± 2.73 3.00b ± 2.10

0.5 4.60c ± 1.12 18.20b ± 4.90

1.0 5.10c ± 1.77 20.40c ± 10.30

1.0 4.15c ± 0.70 26.40c ± 13.80

2.0 1.49d ± 0.26 24.50c ± 12.34

2.0 0.47d ± 0.13 46.20c ± 8.05

4.0 0.61d ± 0.08 44.50d ± 7.61

4.0 0.50d ± 0.11 49.20d ± 9.64 5.0 0.46d ± 0.11 71.60d ± 5.12

F-test ** ** % C.V. 43.57 28.91

**Mean within the same column followed by the same alphabet were not significant difference using DMRT, p≤0.01.

Plantlets were cultured on MS medium supplemented with different concentrations of

sucrose for 10 weeks. It was found that all parameters: number of plantlets, bulbil sized,

length of stolon, number of nodes, number of flowers and sized of flowers were significant

difference ( p≤0.05) (Table 3). Two and Three percentage of Sucrose gave the best result that

gave the highest number of plantlets (10.5 – 10.75 plantlets, respectively) (Figure 5), number

of nodes (10.75 – 10.50 nodes per, respectively) and length of stolon (29.25-28.5 mm,

respectively). The biggest sized of bulbil were formed at 9–10 percentage of sucrose (18.65–

19.05 mm, respectively) (Figure 4). At the ninth week, plant were flowering in the MS

medium only contained 9-10 percentage of sucrose. Ten percentage of sucrose gave the

highest number of flowers and the biggest sized of flower, also (Figure 3).


Table 3: Effect of sucrose concentration on number of plantlets, bulbil size, length of stolon , number of nodes, number of flower, and size of flowers after culture for 10 weeks.

Sucrose (%)

No. of plantlets Size of Bulbil (mm)

Length of stolon(mm)

Number of nodes

Number of flowers

Size of flower (cm)

2 10.75a ± 1.50 9.72e ± 0.92 29.25a ± 0.96 10.75a ± 0.96 - - 3 10.50ab ± 1.73 9.92e ± 0.82 28.50a ± 0.58 10.50a ± 0.58 - - 4 5.50d ± 0.58 11.22de ± 1.21 26.50a ± 1.29 8.25b ± 0.96 - - 5 9.50abc ± 4.20 13.05cd ± 0.31 19.25b ± 0.96 7.75b ± 1.89 - - 6 6.50cd ± 1.29 16.07b ± 0.70 19.50b ± 1.91 8.00b ± 0.81 - - 7 7.75bcd ± 1.26 14.80bc ± 1.98 19.25b ± 2.22 7.50b ± 0.58 - - 8 8.75bcd ± 0.65 15.32bc ± 0.52 20.25b ± 1.70 8.25b ± 0.50 - - 9 9.25abcd ±0.96 18.65a ± 0.47 18.50b ± 1.00 8.00b ± 0.82 0.50b ± 0.57 2.80b ± 3.23 10 12.75a ± 0.65 19.05a ± 1.97 13.25b ± 2.36 7.75b ± 1.25 4.75a ± 0.95 6.07a ± 1.00

F-test * * * * * * % C.V. 19.96 8.09 7.23 11.88 30.10 60.29

Figure 3: Characteristic of Oxalis versicolour flower (the end of arrow) which cultured in

MS medium supplemented with 10 % sucrose.

Figure 4: Characteristics of Oxalis versicolour bulbil cultured in MS medium supplemented

with various concentrations of sucrose. A 2%sucrose, B. 3% sucrose, C.4%sucrose, D.5% sucrose , E. 6%sucrose, F.7%sucrose, G. 8%sucrose, H.9% sucrose, I.10% sucrose.

(bar = 1cm)


231



Figure 5: Various Characteristics of Oxalis versicolour after cultured on MS medium with

various concentration of sucrose. A - plantlets which cultured in MS medium with free sucrose, B- Plantlet in MS medium with 10% sucrose.

5. Discussion Since the callus initiation and regeneration was depend variously on cultivated varieties,

explants and growth regulators used in culture media (Kamo 1994, 1995). The result showed that callus transferred to MS medium supplemented with various concentrations of NAA and BA formed different characters. After cultured for 4 weeks, callus regeneratedto be new shoots and the highest number of plantlets was in MS medium and supplemented with 0.4 mg/l NAA and 0.5mg/l BA, the longest Average length of stolon and number of plantlets were from MS medium supplemented with 0.1 mg/l NAA and 0.1 mg/l BA. This result was the same as Jala and Wassamon (2012) did in Gynostemma pentaphyllum, Gladiolus (Jala, 2013), and Globba sp. ( Jala et al.,2013).

The result in this experiment showed that when cultured explants of Oxalis versicolour

on MS medium supplemented with different concentration of (2, 3, 4, 5, 6, 7, 8, 9, 10 %) sucrose, the result showed that all parameters were significant difference (p≤0.05). The stimulation on bulbil sized, stolon length, number of node as Murashige and Skoog(1962) described their medium. Sucrose is the most common carbon source as well as anosmotic agent for plant tissue and organ culture. Sucrose also supports the maintenance of osmotic potential and the conservation of water in cells. However, high sucrose concentration in the media restricts the photosynthetic efficiency of cultured plants by reducing the levels of chlorophyll, key enzymes for photosynthesis and epicuticular waxes promoting the formation of structurally and physiologically abnormal stomata (Hazarika, 2006). On the other hand, earlier studies have shown that plantlets growing under tissue culture conditions do not fix enough CO2 to sustain growth in the absence of sucrose, which is mainly due to limited CO2 inside the vessel (Gautheret, 1955). Media with 3% sucrose have been the staple since Murashige and Skoog (1962) described their MS medium. Indeed, sucrose concentrations above 2.5 % repress proliferation of callus of various plants (Malamug et al., 1991). Low concentrations of sucrose favor the initiation of numerous shoots in tobacco callus and

A B 1cm 1cm


http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0085989%23pone.0085989-Murashige1

depress the growth of callus (Barg et al., 1977). The effect of high concentration of sucrose are especially when conditions in vitro are in adequate for significant photosynthesis (Muller et al., 2011). The result showed that plantlets in the bottle were flowering by increasing concentrations of sucrose (Table 3). This result was the same as Aloni et al., (1996,1997) mentioned that light perceived by the plant increased the availability of sucrose to the flowers due to increase photosynthesis and translocation. Sucrose had taken up but the sink organ is metabolized, and Zrenner et al.,(1995) studied and indicated that sucrose synthase is a regulatory enzyme that controls sucrose cleavage and starch biosynthesis in sink tissue.

6. Conclusion Young leaves and stem nodes of Oxalis versicolour were used as explants and cultured

on MS medium supplemented with different concentration of 2,4-D. It was found that callus were proliferated at the base of explants and 0.1 mg/l 2,4-D gave the biggest sized of callus(4.6 mm) and their color was light green. Callus transferred to MS medium supplemented with various concentrations of NAA and BA. Callus regenerated to be new shoots and maximum shoots was formed in MS medium supplemented with 4.0 mg/l NAA and 5.0 mg/l BA. Plantlets were cultured on MS medium supplemented with different concentrations of sucrose (2, 3, 4, 5, 6, 7, 8, 9, 10 %) for 10 weeks. It was found that 2and 3% sucrose gave the best result in number of plantlets, bulbil sized, length of stolon, number of nodes. Only nine and ten percentages of sucrose gave flowers. Ten percentages of sucrose gave the highest number of flowers and the biggest sized of flowers.

7. References Aloni B, L. Karni, Z. aidman, A.A. Schaffer. 1996. Changes of carbohydrates in pepper

(Capsicum annuum L.) flowers in relation to their abscission under different shading regimes. Annals of Botany 78: 163-168.

Aloni, B., Z. Aloni, L. KarniI, Z., and A. A. Schaffer. 1997. Relationship between Sucrose Supply, Sucrose-cleaving Enzymes and Flower Abortion in Pepper. Annals of Botany 79: 601 – 605.

Altman, A., R. Goren. 1971. Promotion of callus formation by abscisic acid in citrus bud cultures. Plant Physiol 47: 844-846.

Arigita L, M.J. Cañal, T.R. Sánchez, A. González . 2010. CO2-enriched microenvironment affects sucrose and macronutrients absorption and promotes autotrophy in the in vitro culture of kiwi (Actinidia deliciosa Chev. Liang and Ferguson). In Vitro Cell Dev-Pl 46: 312–322.

Barg, R. and N. Umiel. 1977. Effects of sugar concentrations on growth, greening and shoot formation in callus cultures from four genetic lines of tobacco. Z Pflanzenphysiol 81: 161-166.


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Dragan, V. and B.S. Vinterhalte. 1999. Hormone-Like Effects of Sucrose in Plant in vitro Cultures. Phyton (Austria) Special issue: Plant Physiology".v39: 57-60.

Hazarika BN (2006) Morpho-physiological disorders in in vitro culture of plants. Sci Hort 108: 105–120.

Jala, A. and Wassamon Patchpoonporn. 2012. Effect of BA and NAA and 2,4-D on Micropropagation of Jiaogulan(Gynostemma pentaphyllum Makino). International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies. 3(4):363-370.

Jala, A. 2013 The Effect of the 2,4-Dichlorophenoxy Acetic Acid, Benzyl Adenine and Paclobutrazol, on Vegetative Tissue-Derived Somatic Embryogenenesis in Turmeric (Curcuma var. Chatti). International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies. 4(2):105-111.

Jala, A., Nattapong Chanchula and Thunya Taychasinpitak. 2013. Multiplication New Shoots from Embryo Culture on Globba spp. ). International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies. 4(3):207-214.

Kamo K. 1994. Effect of phytohormones on plant regeneration from callus of Gladiolus cultivar “Jenny Lee”. In Vitro Cell. Dev. Biol. 30P : 26 - 31.

Kamo K. 1995. A cultivar comparison of plant regeneration from suspension cells, callus, and cormel slices of Gladiolus. In vitro Cell. Dev. Biol. 31P : 113 - 115.

Malamug J.J.F., H. Inden and T. Asahira. 1991. Plantlet regeneration and propagation from ginger callus. Scientia Hort. 48: 89–97.

Muller B, Pantin F, Génard M, Turc O, Freixes S, et al. (2011) Water deficits uncouple growth from photosynthesis, increase C content, and modify the relationships between C and growth in sink organs. J . Bot. 62: 1715–1729.

Murashige, T . and F.A. Skoog. 1962. A revised medium for rapid growth and bioassays with tobacco tissue culture. Physiol. Plant. 15 : 473 - 492..

Gautheret R.J.1955. The nutrition of plant tissue cultures. Annu Rev Plant Phys. 6: 433–484.

Zrenner R, Salanoubat M, Willmitzer L, Sonnewald U. 1995. Evidence of the crucial role of sucrose synthase for sink strength using transgenic potato plants. Plant Journal 7: 97-108.

Nattapong CHANCHULA is a PhD candidate in Department of Horticulture, Faculty of Agriculture, Kasetsart University, Bangkhen, Bangkok, THAILAND. His main research is in Plant cell technology and floriculture crop improvement.

Dr. Tassanai JARUWATTANAPHAN obtained her PhD in Biology (Plant Systematic and Evolution) from Chiba University, Japan. He is working at Department of Horticulture, Faculty of Agriculture, Kasetsart University, Bangkhen, Bangkok, THAILAND. His research interests have encompassed plant systematics, plant molecular phylogenetic, plant cytogenetic, and biodiversity of horticulture crops.

Dr. Anchalee JALA is an Associate Professor in Department of Biotechnology, Faculty of Science and Technology, Thammasat University, Rangsit Campus, Pathumtani , THAILAND. Her teaching is in the areas of botany and plant tissue culture. She is also very active in plant tissue culture research.

Peer Review: This article has been internationally peer-reviewed and accepted for publication according to the guidelines in the journal’s website.



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Preparation of Activated Carbon from Sindora Siamensis Seed and Canarium Sublatum Guillaumin fruit for Methylene Blue Adsorption

Samarn Srisa-ard a*

a Department of Chemistry, Faculty of Science and Technology, Rajabhat Maha Sarakham University,

THAILAND A R T I C L E I N F O

A B S T RA C T

Article history: Received 02 June 2014 Received in revised form 20 June 2014 Accepted 23 June 2014 Available online 24 June 2014 Keywords: scanning electron microscope; Langmuir isotherm model; Adsorption isotherm; Chemical activation; Iodine number; Zinc chloride; MB; SEM.

Activated carbons produced from Sindora Siamensis (SSAC) seed and Canarium Sublatum Guillaumin (CSGAC) fruit were prepared by chemical activation with zinc chloride, their characteristics and their methylene blue (MB) adsorptions were investigated. The effects of zinc chloride concentrations and activation temperatures were examined. The surface chemical characteristics of activated carbons were determined by scanning electron microscope (SEM). Adsorption capacity was demonstrated with iodine numbers. The Langmuir and Freundlich equilibrium isotherm theories were applied to describe MB adsorption. The equilibrium adsorption results were complied with Langmuir isotherm model and its maximum monolayer adsorption capacity for SSAC and CSGAC are 672.6 and 487.6 mg/g for MB adsorption. The value of RL was found to be below 1.0, indicating that the resultant activated carbon was favorable for MB adsorption. These results indicate that SSAC and CSGAC shells could be utilized as a renewable resource to develop activated carbon which is a potential adsorbent for MB.


1. Introduction Activated carbon is the most commonly use and most effective adsorbent because of its

high adsorptive capacity (Chen et al., 2003; Daifullah et al., 2007). Therefore, it has been

widely used as adsorbent (Hung et al., 2005) and in catalysis (Lee et al., 2006) or separation


*Corresponding author (S. Srisa-ard). Tel: +66-43-754246. E-mail: [email protected]. 2014. International Transaction Journal of Engineering, Management, & Applied Sciences &

Technologies. Volume 5 No.4 ISSN 2228-9860 eISSN 1906-9642. Online Available at http://tuengr.com/V05/0235.pdf.

235



processes (Rodriguez-Reinoso et al., 2002) such as purification of drinking water, treatment

of exhaust gas and waste water. However, its application fields are restricted due to its high

cost. Presently, the use of low cost plants and agricultural wastes is considered promising

adsorbents for adsorption applications. In recent years, a lot of research has been reported on

activated carbons from plants or agricultural wastes, such as olive mill waste (Abdelkreem,

2013), seaweed (Rathinam et al., 2011), cherry stones (Jaramillo et al., 2009), fluted pumpkin

seed shell (Verla et al., 2012), fluted pumpkin stem waste (Ekpete et al., 2011), rice straw

(Gao et al., 2011), cattail (Shi et al., 2011), coconut husk (Tan et al., 2008), coconut shells

(Yang et al., 2010), tobacco residues (Kilic et al., 2011), sugar cane bagasse, and sunflower

seed hull (Liu et al., 2010), etc.

The Sindora Siamensis (SS) and Canarium Sublatum Guillaumin (CSG) are a large

evergreen tree found in open semi–deciduous forests in Cambodia, Laos, Malaysia, Thailand,

and Vietnam. The diagnostic characters of SS are deciduous or evergreen tree, bark smooth to

slightly fissure. Leave compounds rachis swollen at the base. Flower in panicle is yellow–

green. Fruit an ovoid–round spiny, flattened pod often with blobs of white resin (Sam et al.,

2004). The CSG is 20–35 m tall. Branchlets are brown tomentose when young, glabrescent,

lenticellate, with conspicuous leaf scars.

The objective of this study is to produce activated carbon from a Sindora Siamensis

(SSAC) seed and Canarium Sublatum Guillaumin (CSGAC) fruit by chemical activation

using ZnCl2 and adsorption capacity of activated carbons are also investigated. ZnCl2, as an

important chemical activating agent, has been widely used in the process of activated carbon

preparation (Horng et al., 2010; Rathinam et al., 2011; Gao et al., 2013). It is an efficient

dehydration reagent that promotes the decomposition of carbonaceous material, induces the

charging and aromatization of the carbon, restricts the formation of tar and increases the

carbon yield. Thus to our best knowledge, however, have not yet been reported the activation

of SS seed and CSG fruit with ZnCl2 chemical activation. The major novelty of this work is

the production of activated carbons from ZnCl2 impregnated SS seed and CSG fruit samples

by chemical activation technique in various SS/ZnCl2 and CSG/ZnCl2 ratios and a

temperature range of 500–700°C. The study covers the effect of operating parameters such as

temperature of activation and impregnation ratio on the product quality. The product quality is

characterized based on the iodine number and MB adsorption isotherm.

236 Samarn Srisa-ard

2. Experiment

2.1 Materials and Preparation of Activated Carbon Sindora Siamensis seed and Canarium Sublatum Guillaumin fruit were collected from

Maha Sarakham province of Thailand. The precursor was crushed and sieved in order to get a

standardized particle dimension. Five to forty grams of ZnCl2 were dissolved in 200 mL of

distilled water, and then 20 g of raw ash was mixed with the ZnCl2 solution and stirred at

approximately 85°C for 2 hr. The mixtures were dehydrated in an oven at 110°C for about 24

hr. The resulting activated carbons were then chemically activated at 500, 600 and 700°C for

3 hr in atmosphere. The activated samples were washed in 3 M hydrochloric solution by

heating at around 90°C for 30 min to remove the zinc compounds. Then, they were washed

several times with warm distilled water, and finally with cold distilled water. The washed

samples were dried at 110°C for 24 hr to prepare the activated carbons. Each sample was

stored in sealed bottle vial.

2.2 Sample Characterization The iodine number is a technique employed to determine the adsorption capacity of

activated carbons. The iodine number indicates the porosity of the activated carbon and it is

defined as the amount of iodine adsorbed by 1 g of carbon at the mg level. Iodine number can

be used as an approximation for surface area and microporosity of active carbons with good

precision. The iodine adsorption was determined using the sodium thiosulfate volumetric

method (ASTM, 2006). It is a measure of activity level (higher number indicates higher

degree of activation), often reported in mg/g. It is a measure of the micropore content of the

activated carbon by adsorption of iodine from solution (Elliott et al., 1989). The procedure of

the iodine number determination is as follows: activated carbons were weighed out into

conical flasks (sample weight ranged between 100 and 400 mg). Ten millilitres of 5% (in

weight) hydrochloric acid solution were added to each flask and then mixed until the carbon

became wet. The mixtures were then boiled for 30 s and finally cooled. One hundred

millilitres of 0.05 M standard iodine solution were added to each flask. The contents were

vigorously shaken for 30 s and then immediately filtered. A 50 ml aliquot of each filtrate was

titrated by a standardized 0.1 M sodium thiosulfate solution. The morphologies of SSAC and

CSGAC were examined by a LEO/1450 scanning electron microscope (SEM). The samples

were dried at 105°C for 2 hr and coated with a thin gold film to give electrical conduction on

the carbon external surface.



237



2.3 Adsorption Isotherm Methylene blue kinetic and isotherm adsorption experiments were carried out to evaluate

the adsorption performance. The equilibrium adsorption research was completed by adding a

fixed amount of activated carbon into 25 ml different initial concentrations of MB. The

kinetic adsorption studies were performed by adding 0.2 g activated carbon into 200 ml

different initial concentrations of MB. The aqueous samples were taken at pre–set time

intervals and their concentrations were determined. Concentration determination of all the

samples was filtered before they were measured by UV spectrophotometer (Perkin

Elmer/lamda 12) at the maximum absorption wavelength of 664 nm.

The Langmuir and Freundlich equilibrium isotherm theories were applied to describe the

MB adsorption. Langmuir equation can be represented by the following Eq. (1) (Singh et al.,

2008; Fierro et al., 2008):

e

e

qC =

maxmax

1QC

QKe

L

+ (1)

where Ce (mg/L) is the equilibrium concentration of MB in solution, qe (mg/g) is the amount

of MB adsorbed at the equilibrium time, Qmax (mg/g) is the maximum capacity, and KL

(L/mg) is the Langmuir constant related to the free energy or net enthalpy of adsorption.

Freundlich model is an empirical equation assuming heterogeneous adsorptive energies

on the adsorbent surface, which can be written as Eq. (2) (Valente et al., 2011):

log qe = log KF + 1

𝑛log Ce (2)

where KF is the Freundlich constant and taken as an indicator of adsorption capacity, in

(L/mg) and 1/n is an empirical constant related to the magnitude of adsorption driving force

(Fan et al., 2008).

3. Results and Discussion

3.1 Production Yield The production yields (%yield) of SSAC and CSGAC are listed in Table 1, the yield

values of SSAC were 85.26, 75.26, and 72.86% for activated at 500, 600, and 700°C,

respectively. The yield values of CSGAC were 84.94, 77.46, and 73.02% for activated at 500,


600, and 700°C, respectively. It is obviously seen that the yield decreases with increasing

temperature. As generally recognized, O and H atoms could be evolved into CO, CO2, H2O,

CH4, aldehydes or tar in the carbonization process of lignocellulosic materials. Moreover, the

yield is slightly difference in various ZnCl2/SS or ZnCl2/CSG ratios. Hence, the yield

depends on the amount of carbon removed by combining with O and H atoms. However,

ZnCl2 would selectively stripe H and O away from SSAC and CSGAC as H2O and H2 rather

than CO, CO2 or hydrocarbons (Caturla et al., 1991).

Table 1: Yield (%) and capacity of the prepared carbons in the adsorption of iodine numbers.

Temperature (°C)/Types of activated carbon

Yield (%) Iodine number (mg/g)

SSAC CSGAC SSAC CSGAC 500 85.26 84.94 148.23 146.33 600 75.26 77.50 147.40 142.09 700 72.86 73.02 132.24 118.58

3.2 Iodine Number The capacities of the prepared carbons in the adsorption of iodine with SSAC and

CSGAC are list in Table 1. It is found that the iodine numbers for iodine adsorbed on SSAC

were 148.23, 147.40, and 132.24 mg/g for activated at 500, 600, and 700°C, respectively and

iodine numbers for iodine adsorbed on CSGAC are 146.33, 142.09, and 118.58 mg/g for

activated at 500, 600, and 700°C, respectively. This data indicate that the activated carbon

prepared from SS is more suitable for iodine adsorption than CSGAC, which the preparation

of activated carbon at 500°C is the highest porosity in both SSAC and CSGAC. The tested

activated carbons adsorb significant amounts of iodine which are strongly related to the

degree of activation.

3.3 Textural Characterization by SEM The morphology in terms of amorphous, pore size and pore distribution of SSAC and

CSGAC was investigated. The SEM photographs of raw ash, SSAC and CSGAC for

activation at 500–700°C are shown in Figures 1 and 2. The result showed that the highly

amorphous structure could be prepared from the SS seed and CSG fruit. The fibrillary

structures of all SSAC and CSGAC reveal that the pores are not cross–linked. Figure 1a–1d



239



Figure 1: SEM micrographs for (a) raw ash, (b) SSAC for activated at 500°C, (c) SSAC for

activated at 600°C and (d) SSAC for activated at 700°C

Figure 2: SEM micrographs for (a) raw ash, (b) CSGAC for activated at 500°C, (c) CSGAC

for activated at 600°C and (d) CSGAC for activated at 700°C

shows that the surface of SSAC is relatively organized with large pores. Whereas, Figure 2a–

2c indicates the external surface of CSGAC is similarly to SSAC but for CSGAC activated at

700°C (see Figure 2d) giving small pore volumes. It has been suggested that the cavities

resulted from the evaporation of ZnCl2 during carbonization, leaving the space previously

occupied by the ZnCl2 (Hu et al., 2001).


3.4 Methylene Blue Adsorption Capacity The Langmuir and Freundlich equilibrium isotherm theories were applied to describe the

MB adsorption. Langmuir equation can be represented by the following Eq. (1). Freundlich

model is an empirical equation assuming heterogeneous adsorptive energies on the adsorbent

surface, which can be written as Eq. (2). The essential features of Langmuir isotherm can be

expressed by the term of separation factor or equilibrium parameter (RL), which is defined as

RL = 1/(1 + KLC0) (where C0 is the initial concentration of adsorbate and KL is its Langmuir

constant). The RL value refers to the nature of adsorption as irreversible (RL = 0), favorable (0

< RL < 1), linear (RL = 1) or unfavorable (RL > 1) (Bouhamed et al., 2012; Liu et al., 2010).

The Langmuir and Freundlich calculated parameters are given in Tables 2 and 3. The qe

values of SSAC for activated at 500, 600, and 700°C were 441.6, 672.6, and 462.6 mg/g,

respectively. And the qe values of CSGAC for activated at 500, 600, and 700°C were 429.3,

487.6, and 203.8 mg/g, respectively. This data indicate that the activated carbon prepared

from SS is more suitable for iodine adsorption than CSG, which the preparation of activated

carbon at 600°C is the highest porosity in both SSAC and CSGAC. The values of RL are

found to be below 1 for MB adsorption, indicating that the resultant activated carbons were

favorable for MB adsorption. Average correlation coefficients R2 for SSAC and CSGAC

were 0.95 and 0.89, respectively, indicating that the two models fits to the experimental data.

The Freundlich isotherm model shows a better description for MB adsorption data with

average R2 for SSAC and CSGAC in the range of 0.95 and 0.87, respectively. Freundlich

parameters KF and 1/n were obtained from the slope and intercept, respectively, which

demonstrate whether the adsorption is favorable or not. A high value of KF, is indicative of a

high adsorption capacity (Salame et al., 2003). In short, 1/n is a measure of the surface

heterogeneity, ranging between 0 and 1, as its value gets closer to zero, the surface become

more heterogeneous (Ahmaruzzaman et al., 2005). Since all the value of 1/n is less than 1, it

indicates a favorable adsorption (Mohanty et al., 2005).

The lower determination SSAC coefficients R2 of the Langmuir suggest that the

isotherm data do not fit the Langmuir model. The higher determination SSAC coefficients R2

of the Freundlich equation suggest that the Freundlich equation can be used to fit the

experimental adsorption data and evaluate the maximum dye adsorption capacities of the

three adsorbents. Whereas, the determination CSGAC coefficients R2 of the Langmuir is equal



241



to Freundlich suggesting that the adsorption capacities not difference. The results also

indicate that the adsorption of MB by the three adsorbents takes place in a monolayer

adsorption manner.

Table 2: Parameters of Langmuir adsorption isotherm models for MB adsorbed by the

different temperatures. Temperature (°C)/Types of

activated carbon

SSAC CSGAC Qe

(mg/g) KL

(L/mg) RL R2 Qe (mg/g)

KL (L/mg) RL R2

500 441.6 0.075 0.382 0.9302 429.3 0.043 0.510 0.8942 600 672.6 0.078 0.373 0.9554 487.6 0.120 0.285 0.7909 700 462.6 0.091 0.340 0.9597 203.8 0.009 0.822 0.9997

Table 3: Parameters of Freundlich adsorption isotherm models for MB adsorbed by the different temperatures.

Temperature (°C)/Types of activated carbon

SSAC CSGAC KF

(L/mg) 1/n R2 KF (L/mg) 1/n R2

500 2.077 0.391 0.9798 5.941 0.348 0.8729 600 2.228 0.315 0.9583 5.906 0.409 0.3254 700 2.008 0.409 0.9247 3.862 0.658 0.9315

4. Conclusion Activated carbons were produced from Sindora Siamensis seed and Canarium Sublatum

Guillaumin fruit by chemical activation with zinc chloride, their characteristics and their

methylene blue adsorptions were investigated. The effects of zinc chloride concentrations and

activation temperature were examined. The morphology, pore size, and pore distribution

characteristics of activated carbons were determined by SEM method. Adsorption capacity

was demonstrated with iodine numbers. The Langmuir and Freundlich equilibrium isotherm

theories were applied to describe methylene blue adsorptions. The equilibrium adsorption

results were complied with Langmuir isotherm model and its maximum monolayer adsorption

capacity for SSAC and CSGAC are 672.6.0 and 487.6 mg/g for methylene blue adsorption.

The value of RL was found to be below 1.0, indicating that the resultant activated carbon was

favorable for phenol adsorption. These results indicate that SSAC and CSGAC shells could be

utilized as a renewable resource to develop activated carbon which is a potential adsorbent for

methylene blue.


5. Acknowledgement The authors gratefully acknowledge the Department of Chemistry, Faculty of Science and

Technology and Research and Development Institute, Rajabhat Maha Sarakham University

for financial support of this research.

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Samarn Srisa-ard works at the Department of Chemistry at Rajabhat Maha Sarakham University. He received a B.Sc. in Chemistry from Khon Kaen University, THAILAND, and M.Sc. in Physical Chemistry from Chiangmai University, THAILAND. Mr. Srisa-ard is interested in applications of chemistry in everyday life.




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Use of Filter Media Made from Vetiver Grass Root Ash for Water Treatment Krittiya Lertpocasombut a* and Maruay Onsod a, b

a Department of Civil Engineering, Faculty of Engineering, Thammasat University Rangsit Campus, Pathumtani 12120, THAILAND b Quality System & Product Auditing Manager, Goodyear (Thailand) Public Co. Ltd., Pathumtani, 12120, THAILAND A R T I C L E I N F O A B S T RA C T Article history: Received 18 June 2014 Received in revised form 06 July 2014 Accepted 09 July 2014 Available online 11 July 2014 Keywords: natural material; polyvinyl alcohol; pellet; turbidity;

Vetiver grass and its usages have been widely reported in many researches. This research aimed to use the vetiver grass root ash (VGRA) to filter water to improve its quality. The investigation of the physical and chemical properties of the VGRA indicated the product from natural material ash could be used as a filter medium. The distribution of particle size, the specific gravity, and the Iodine number of the VGRA were determined as well as the ratio of the VGRA to polyvinyl alcohol (PVA) as a binding polymer were analyzed. The results revealed that the best mold of the VGRA pellet as a filter media was a circular shape. The ratio of the VGRA to PVA was 7.33 to 1. This was consistent with the results of the linear shrinkage that were 13.35 ± 2.10 which was the best form of the VGRA product to be used as a filter medium for water turbidity treatment.


1. Introduction The water used must be safe and free from dangerous bacteria. It is necessary to have the water

quality meet the required standard. The use of plants to improve water quality is one method that has

received considerable attention. In general, natural materials are cheap and readily available in every

country. Many researchers [1][2][3] have reported both viable or nonviable properties of vetiver grass

and its usages. Vetiver grass is regarded as a miracle plant that is the subject of ongoing research.

This research focuses on studying the properties of vetiver grass root ash to produce the filter material

suitable for improving water quality. The filter material was formed with polyvinyl alcohol at various


*Corresponding author (Krittiya Lertpocasombut). Tel: +66-2-5643005 x3109. E-mail: [email protected]. 2014. International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies. Volume 5 No.4 ISSN 2228-9860 eISSN 1906-9642. Online Available at http://tuengr.com/V05/0247.pdf.

247



percentages for the purpose of studying the performance of the filter media produced in terms of the

linear shrinkage, the porosity and the apparent density of the product. Then the product selected was

used as a filter media for water turbidity treatment.

2. Materials and Methods

2.1 Materials and Chemicals The vetiver grass used was grown for at least 18 months with a length of root not less than 0.50

m. The polyvinyl alcohol (PVA) used was commercial grade with the molecular weight of 30,000 –

50,000. Water used for the experiment was deionized water.

2.2 Preparation of the Vetiver Grass Root Root of vetiver grass of Nakhon Sawan species was chosen due to its availability and

abundance. It was washed thoroughly five times with clean water and then dried under the sun

for at least 48 hours. The dried root was burned at 550 ºC for 15 to 30 minutes and ground for

size reduction in a laboratory blender at a speed of 3,000 rpm for 15 minutes. At this stage,

the properties of the vetiver grass root ash (VGRA) were determined for the particle size

distribution following the ASTM D2862 Standard test method, the specific gravity of soil

solid by water pycnometer following the standard ASTM 854, and the Iodine number

following the standard ASTM D4607.

2.3 The VGRA Pellet The VGRA particles were sifted through a sieve of 50, 100 and 200 mesh sizes, divided into 3

sieve sizes and combined with PVA in ratios varying from 6 to 18 % wt. by wt. The slip behavior flow

of the 3 sieve sizes of the VGRA with various percentages of PVA was determined. The linear

shrinkage of the VGRA pellet formed was taken into account after drying at 125 ºC for 2 hours.

2.4 Experimental Setup for Water Turbidity Removal Figure 1 shows a schematic diagram of the experimental set up. It was comprised of 3-filter units,

and a receiving vessel attached to available suction pump.

Figure 1: The schematic diagram of the experimental unit.

The raw water sample was taken from the natural river source at the intake of the water supply

248 Krittiya Lertpocasombut and Maruay Onsod

plant located in Pathum Thani province in Thailand. The inlet and exit water turbidity of the filtration

unit was measured by UV spectrophotometer. The pressure, the flow rate and the particles capture

performances were measured under the experimental conditions.

3. Results and Discussions

3.1 The Physical and Chemical Properties of the VGRA After grinding, the composition of the ash of the vetiver grass root was determined by XRF

following the Standard ASTM C114 and results are shown in Table 1.

Table 1 The chemical composition of the VGRA. Chemical Composition % Weight % Standard Error Carbon Dioxide (CO2) 52.67 0.16 Silicon Dioxide (SiO2) 44.10 0.14

Aluminum Oxide (Al2O3) 1.03 0.17 Iron Oxide (Fe2O3) 2.11 0.14

Other 0.10 0.21

It was found that the vetiver grass root ash (VGRA) contained 44.10 % silicon dioxide

which was similar to that of the results from AIT research group [3] on the use of vetiver

grass ash to replace cement in which composition of silicon dioxide in the ash of the vetiver

grass up to 57.48 % was reported. The silica content in the VGRA makes it feasible to further

study of the use of roots of vetiver grass as a filter material when combined with a polymer

such as polyvinyl alcohol (PVA), which was selected for this study.

The mean particle size is useful when determining the specific gravity of the substance.

Root of the vetiver grass after burning at 550 °C was crushed in a laboratory blender to a

mean particle size of 0.068 ± 0.003 mm by sieve analysis. This size is similar to fine sand

(0.05-0.25 mm).

The specific gravity of the VGRA by the ASTM standards for classification was found to

be in the range of 2.26 to 2.60. It was comparable to the compounds like carbon (2.26),

gypsum (2.3), clays (2.6), sand and silica (2.6), with a similar specific gravity.

Three sieve sizes (50, 100 and 200 mesh) of VGRA were evaluated for Iodine number

according to the ASTM standards. This value was considered to examine the assumption that

the VGRA has the ability to adsorb. The results showed that the Iodine number of the VGRA

(36 - 46 g/kg) was comparable to the standard carbon N550 and N660. The VGRA of 200

*Corresponding author (Krittiya Lertpocasombut). Tel: +66-2-5643005 x3109. E-mail: [email protected]. 2014. International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies. Volume 5 No.4 ISSN 2228-9860 eISSN 1906-9642. Online Available at http://tuengr.com/V05/0247.pdf.

249



mesh sieve size, which was comprised mostly of the smallest particle size, gave the highest

Iodine adsorption number.

3.2 The Ratio of the VGRA to PVA Pellets of VGRA were formed by casting. The VGRA of sieve sizes 50, 100 and 200 mesh were

combined with the PVA to give concentrations of 6, 8, 12 and 18 % in order to measure the flow

behavior and stability of the slip. The results are shown in Figure 2.

Figure 2: Plastic viscosity values of the VGRA slip at different ratios of PVA.

Figure 3: The linear shrinkage of the VGRA of 3 sieve sizes at different ratios of PVA.

R2 values ranging from 93 to 99 % were obtained for all ratios of the VGRA to PVA. The

maximum R2 value was found with the mixture of 12 % PVA producing the optimum flow and

stability of the slip.

y = 0.1189x + 52.61 R² = 0.9577

y = 0.0733x + 88.497 R² = 0.9924

y = 0.2436x + 115.27 R² = 0.9681

y = 1.0029x + 148.25 R² = 0.9286

Plas

tic V

isco

sity

(mPa

s)

Mesh Number

PVA 18 %PVA 12 %PVA 8 %PVA 6 %

y = -66.571x + 42.503 R² = 0.7555

y = -73.595x + 21.445 R² = 0.8594

y = -127.62x + 25.488 R² = 0.5476

(%sh

ringk

age)

Concentration of PVA (%)

50 Mesh

100 Mesh

200 Mesh


3.3 The Linear Shrinkage of the VGRA Pellet Hollow casting was used to test for the linear and volumetric shrinkages of the VGRA which had

been combined with PVA in different ratios to form a pellet. The results are shown in Fig. 3.

The VGRA of 100 mesh sieve size showed the highest coefficient of determination with 86 %

corresponding to the VGRA to PVA ratio of 7.33 to 1.

3.4 The Capability of the VGRA Filter Media A water volume of 0.25 L was filtered through the VGRA pellets produced from 50, 100 and 200

mesh sieve sizes with the PVA content of 12 % and a constant pressure of 2 bars.

With the filtration pressure constant, the flow rates of water filtered through the 3 sets of VGRA

pellets declined as the mesh number of the VGRA pellets increased from 50, 100 and 200 mesh. The

flow rates were 444, 309 and 151 L/m2 · h, respectively. On comparing these values with the flow

rates of microfiltration membrane (10 – 20 L/m2 · h) [4], they were about 10 times higher. The flow

rate decreased similarly when the water was filtered through the VGRA pellets under a constant

pressure of 7 bars as well. However, all VGRA pellets produced from 50 mesh were cracked as were

some of the 100 and 200 mesh pellets also.

The efficiency of particles capture was 67, 73 and 73 % and their residual values were 67, 55 and

54 ppm respectively under a pressure of 2 bars. No similar research on filter media has been found to

make a comparison. One explanation of the effect of removal of coliform bacteria (as suspended solid)

with modified homemade filter media could be that as the treatment time progressed, the adsorbent

sites of the media had a tendency towards saturation [5].

3.5 The Effects of Turbidity on the VGRA Filter Media With the constant pressure of 2 bars and the water sample used from the natural river source, the

effluent turbidity reached a steady value of 30 ± 1 NTU when flowing through the VGRA pellet of

100 mesh sieve size, whereas, the VGRA pellet of 50 mesh sieve size exhibited lower efficiency of

removal turbidity (up to 50 NTU) as shown in Table 2.

Table 2 Turbidity of the water before and after passed through the VGRA pellet.

Turbidity Mesh Number (NTU) 50 100 200 Inlet 122 122 122 Exit 50 31 30

From these results, removal efficiency of 75 % was obtained for inlet turbidity of 122 NTU and a

flow rate of 309 L/m2 · h for filtration using the 100-mesh VGRA pellet with PVA 12 % as the filter

media. *Corresponding author (Krittiya Lertpocasombut). Tel: +66-2-5643005 x3109. E-mail: [email protected]. 2014. International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies. Volume 5 No.4 ISSN 2228-9860 eISSN 1906-9642. Online Available at http://tuengr.com/V05/0247.pdf.

251



4. Conclusions The vetiver grass root ash (VGRA) containing up to 44.10 % of silicon oxide with a mean particle

size of 0.068 mm was used as a filter material. Its specific gravity was in the range of 2.26 to 2.60,

similar to silt and fine sand. The VGRA with 200 mesh sieve size showed acceptable results with the

maximum Iodine number of adsorption, the flow behavior of slip in forming, and a suitable PVA ratio.

However, the linear shrinkage of the VGRA pellet formed with 100 mesh sieve size resulted in the

best coefficient of determination compared to the VGRA pellet with 200 mesh and 50 mesh sieve

sizes, respectively. The filtration experiment confirmed that the 100-mesh VGRA pellet formed with

PVA content of 12 % was the optimal composition as a filter media under 2-bar pressure for water

turbidity removal.

5. References [1] Thiramongkol, V., & Baebprasert, B. The vetiver grass pot: Production and use.

Department of Science Service, Bangkok, Thailand, pp.350-352, www.prvn.rdpb.go.th/files/CP-4-6.pdf, [18 July 2012].

[2] Ash, R., & Truong, P. (2004). The use of vetiver grass for sewage treatment. Sewage Management QEPA Conference, Cairns, Australia, April 5-7, 2004. www.vetiver.com/AUS_ekeshire01.pdf, [18 July 2012].

[3] Nimityongskul, P. & Chomchalow, N. Utilization of vetiver grass as construction materials. AIT. www.prvn.rdpb.go.th/files/7-05.pdf, [18 July 2012].

[4] Lertpocasombut, K. (2004). Hollow fiber microfiltration membrane in activated sludge and its chemical cleaning for water reuse. Proceedings of the International Symposium on the Development of Water Resource Management System in Mekong Watershed, Hanoi, Vietnam, December 3-4, 2004, 46-52.

[5] Devi, R., Alemayehu, E., Singh, V., Kumar, A., & Mengistie, E. (2008). Removal of fluoride, arsenic and coliform bacteria from drinking water by modified homemade filter media. Bioresource technology, 99(7), 2269-2274.

Dr.Krittiya Lertpocasombut is an Associate Professor in the Department of Civil Engineering, Faculty of Engineering, Thammasat University, Thailand. She received a B.Sc. in Chemistry from Chulalongkorn University, Thailand, an M.Sc. in Environmental Engineering, Asian Institute of Technology (A.I.T.), D.E.A. Diplome d’Etudes Approfondies in Water Purification and Treatment Engineering from INSA de Toulouse, France, and a PhD in Water Purification and Treatment Engineering, Institut National des Sciences Appliquees (INSA), Toulouse, France. Dr. Lertpocasombut is interested in water and wastewater treatment; wastewater recycled by membrane technology; water supply sludge treatment and its reuse/recycle.

Maruay Onsod is Quality System & Product Auditing Manager, Goodyear (Thailand) Public Co. Ltd., Thailand. She obtained a B.Sc (Chemistry) from Rajamagala University of Technology (Thanyaburi). She is a master candidate in the Department of Civil Engineering, Faculty of Engineering, Thammasat University. She is interested in water treatment technologies.



http://www.vetiver.com/AUS_ekeshire01.pdf

http://www.prvn.rdpb.go.th/files/7-05.pdf


http://TuEngr.com

A Review of Resource-Constrained Project Scheduling Problems (RCPSP) Approaches and Solutions Mohammad Abdolshah a*

a Engineering Faculty, Islamic Azad University, Semnan Branch, Semnan, Iran

A R T I C L E I N F O A B S T RA C T Article history: Received 17 June 2014 Received in revised form 08 July 2014 Accepted 10 July 2014 Available online 11 July 2014 Keywords: Exact salvation; Heuristics; Meta-heuristics; Deterministic.

Resource-constrained project scheduling problems are one of the most famous proposed problems in operational research and optimization topic. Using of discrete models by considering complexity of the problems requires designing efficient algorithms for solving them. On the other hand, this series of topics and generally project management are given attention in recent decades. Competition features of today’s world, lead in time implementation of project with required quality to be important. Those factors lead to be given attention to resource-constrained project scheduling problems and their solutions theoretically and practically by academic researches and practitioners. The purpose of the paper is determining different methods and approaches that are used for solving the mentioned problems simultaneously or separately. The various described models in literature that consist of more than 200 published papers in most well-known journals, are collected and proposed in table format. In this research by studying these papers, in addition clarifying features of the developed models and the gaps, practitioners of projects implementation in various organizations can choose appropriate model for their projects by considering organizational conditions, types of resources and their organization’s activities’ technological specifications.


1. Introduction Project planning is determination of time sequencing or scheduling plan for conducting a

series of related activities that are constituents of project. In this case, Project disintegrate to some activity by methods like work breakdown structure (WBS). These activities are connected with each other because there are various logical relations between them. Logical and Immediate relations between each two activities are explained by controller like Finish to start (FS) relation,


*Corresponding author (Mohammad Abdolshah). Tel: +98-231-4462198 E-mail address: [email protected]. 2014. International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies. Volume 5 No.4 ISSN 2228-9860 eISSN 1906-9642. Online Available at http://tuengr.com/V05/0253.pdf.

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start to start (SS) relation, finish to finish (FF) relation, and start to finish (SF) relation. Also, in more complicated projects it is possible to define more controllers like parallel implemented between two activities(Hadju, 1997In fact dependence of activities is based on their priority of implementation; it means it is possible that implementation of an activity depends on implementation of the others, this is called that project has priority constraints between activities. But in addition to these limitations, May bean other type of constraints, as resources constraints exist in project. So in project planning in addition to considering priority constraints, planning should be compatible with resources constraints. The objective of scheduling and sequencing activities is optimal allocation of limited resources over time. In fact scheduling is determination of activities which must be done in the specified time and sequencing, determine order of activities which must be done. Those project planning problems which do not have limitations of resources or consider them, are known as project scheduling problems without resource-constrained and those problems which have resource-constrained and these limitations are considered in planning project, called resource-constrained project scheduling problems (RCPSP). This problem is one of the most complicated problems of operation research which has considerable progress in developing exact solution and innovative methods at recent decades and recently new optimization methods are used to solve it” (Mohring et al, 2003).For implementing each activity requires different resources such as time, capital, human power and etc. These resources are often divided into two categories: Renewable like human power and non-renewable such as capital. Each activity can be implemented in several modes such as manually, semi-mechanized and mechanized. Implementation of each mood needs different type and amount of resources (Drexl et al, 1993). In resource-constrained project scheduling problems for implementing each activity like i needs rik unit of resource k = 1,…,m , at per unit of activity’s execution time (di). Meanwhile k resource has bk constraints per unit of time. The parameters (di

,ri , bk)are non-negative and determined. This problem’s objective often is determining start time and mode of implementation of each activity for minimizing the project’s execution time. It is obvious that the problem solution must provide constraints that are related to activities’ logical relations, and consider resource constraints too. There are two optimal and heuristics approach for solving the problem (Herroelen et al, 1998). The realistic solution instances of the problem because of complexity, extension and difficulty with optimal approaches like mathematical planning, dynamic planning or branch and bound, is impractical (Brucker et al, 1998).

2. Solving Methods Before suing of computer in project scheduling problems, researches scheduled projects

manually so it was too time consuming and was not a good guaranty for achieving an optimal result. In the last of 1950 decade, developing critical path techniques and evaluating and overlooking the project led that projects had capability to be described by network diagrams as

254 Mohammad Abdolshah

works and activities were defined by network structure. Nevertheless, within the techniques, only time was considered and limitation of using resources was not studied. Meanwhile project’s constraint is one of the main problems of project planning in real world, during two recent decades types of project scheduling planning techniques under resource constrained conditions were proposed, implemented and controlled which generally are divided to exact and approximate methods. In fact it can be told that resource-constrained project scheduling problem has more than 40 years history. There are two approaches, optimal and heuristics, for solving the problem (Herroelen et al, 1998). Each of the methods has disadvantages and advantages. The exact methods have ability to obtain and guaranty optimal result. In these methods, all solving problem spaces are searched to find optimal answer from solving space. Although essential calculations for these methods are so many and as a results, they are so slow but guaranty the general optimization of problem, in fact the realistic solution instances of the problem because of complexity, extension and difficulty with optimal approaches like mathematical planning, dynamic planning or branch and bound, is impractical (Brucker et al, 1998). Of course the application of optimal approaches for solving smaller instances of the problem are reported in the literature. For instance, the paper refers interested reader to (Deckro et al, 1991) about mathematical planning, to (Icmeli et al, 1996. Carruthers et al, 1996) for numerical methods such as dynamic planning, to (Petrovic 1968, Demeulemeester 1998) about branch and bound methods. And for overcoming the computational problems of the methods, approximate methods are proposed. In these methods, Instead of the whole space of problem solution, a part of it is searched so they do not guaranty the optimal results and try to achieve a good approximate answer but they are quick methods and at the right time they achieve a good answer for huge problems. Many of the heuristics solving approaches for resource-constrained project scheduling problems are studied at 2006 (Kolisch et al, 2006). They categorized the approaches in 4 groups as (1) Priority rule- based approaches like Random sampling (Coelho et al, 2003); (2) Approaches based on meta-heuristics methods such as genetic algorithm (Alcaraz et al, 2003. Tareghian et al, 2007), tabu search algorithm (Nonobe et al, 2002), simulated annealing (SA) algorithm (Valls et al. 2004) ant systems (Merkle et al, 2002); (3) Non – Standard meta-heuristics approaches like scatter search algorithm (Fleszar et al, 2004); and at last (4) approaches based on other heuristics methods such as forward and backward Improvement (FBI) (Tormos et al. 2003), Network analysis (Sprecher, 2002). This paper categorizes solving models that are discussed in past literature, as 3 diagrams

3. Exact solving methods RCPSP are as general format of sequence of operations of NP hard problems type. The


255



optimal solutions, which are mentioned in literature, are: Zero-one mathematical planning and numerical implicit methods such as dynamic planning and branch and bound method. At recent decades, solving the problems is improved widely which are tested in two series problem. These series are: Series of 110 problems designed by Peterson and Series of 480 problems by Klisch. Algorithms are evaluated base on how many problems are solved by them at how much time. The series of Peterson problems include 110 problems instances that are designed by Peterson. Series of problems have 7 to 50 activities and 1 to 3 renewable resources. During last decades, this series was a criterion for evaluating validity and ability of optimal and close to optimal procedure. In 1995, Klisch questioned validity of Peterson’s series that leads to develop ProGen. Network producer software that is able to produce RCPSP pattern with pre-determinate and 30 types of activity and 4 types of renewable resource, see Figure 1.

Figure 1: Exact solution categories

3.1 Heuristics solutions A brief definition of a heuristics method is a technique that search close solutions to optimal

with acceptable computational cost, but in fact unlike the exact solutions which guaranty finding the optimal answer if there are, they do not guaranty for achieving to an optimal result. Heuristics methods sometimes find the optimal answer and most of the time they reach to good answer. And these methods usually require less time and memory than exact solutions. The heuristics in scheduling often are defined as scheduling rules with dispatch rules. Often the rules are complex to be defined and for a specific type of the problem with a special series of restrictions and assumptions, are appropriate. The heuristics are used for searching combinational space of permutations in sequences of tasks or determining the conceivability of allocating resource, time and task during creation of scheduling or combining sequencing and scheduling. Heuristics scheduling are applied on series of tasks and determine at what time

Exact solutions

Mathematical planning

determinsticmethodes

Linear planning

Integer planning

Zero-one method

Numerical methods

Dynamic planning

Branch and Bound

method

Synthetic Methods

Dynamic planning

Critical path - PERT

Simulation

Synthetic

Stochastic

Markov chain

Goal theory

System analysis


which task must be done. If a task can be done in more than one implementation condition or on series of resources, heuristics determines which resource or implementation is used. The heuristics solutions are be used for major problems pattern.

Figure 2: Heuristics methods categories

3.2 Meta-heuristics Solutions During last 20 years, a new type of estimated algorithm has been created which essentially

tries to combine basis heuristics methods with an objective of efficient and effective search in search space in frameworks of upper level. The meta-heuristics methods are the last generations of heuristics algorithms and widely used for solving RCPSP too. In fact, the meta-heuristics are strategies in order to guiding search process. Participant techniques in meta-heuristics algorithms are in range of simple procedure, local search to complex learning processes.

3.2.1 Trajectory Methods

It works on single solutions and includes meta-heuristics based on local search. It means that algorithm start form primary condition (primary solution) and describes a trajectory in search space. Each movement is take place if the result solution is better actual one. Upon finding local minimal, the algorithms end such as Tabu search, iterated local search and variable neighborhood search. Their common features are describing a trajectory in search space during search process.

3.2.2 Population methods They do search process which combine meta-heuristics evolution with exact methods or

Heuristics methods

Search- based

Constructive

Generation scheduling

Parallel scheduling

Serial scheduling

double scheduling

Serial

Parallel

Priority-based

Single pass

Multi pass

priority rule

Forward backward

sampling method

baised random sampling

regret bsed random

sampling

random sampling

Improvement

Neighborhood search

forward backward improvment

Based on exact methods

decomposition

iteratation

column generation

relaxation

exact method

Lagrange

Hybrid Combination

withith several heuristics


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other meta-heuristics, and combination of types of heuristics and meta heuristics in order to achieving optimal answers, can be observed in meta-heuristics methods, Figure 3.

Figure 3: Meta Heuristics methods categories

4. Approaches Most of the studies in planning and project scheduling assume that there are complete

information for solving scheduling problem which must be solve and the obtained basis scheduling plan will be implemented in a static environment too. Although there are many uncertainly in a relation with activities implementation that take place with implementation of project gradually which includes the following categories in diagram? In this section, there is review of basis approaches in project planning and scheduling at exact and unreliability conditions. It will be discussed about application potential of each of the methods in project uncertainly planning with definitive network structure. Figure 4 show types of RCPSP approaches.

Figure 4: Types of RCPSP approaches

4.1 Deterministic approach In this approach, all problems’ parameters are assumed definitive and determined and it has

Types of approaches on RCPSP

Deterministic Non- Deterministic

Reactive Proactive (Robust) Stochastic Fuzzy Sensetive

analyse

Number of approaches

disceret Integrated


rich position in RCPSP literature and is used for relaxation of the assumption in most of the papers. These kinds of papers because of simplifying real conditions have defects and practically, restrict efficiency of model in real projects.

Figure 5: FRCPSP categories.

4.2 Proactive (Robust) approach Objective of the proactive scheduling is producing basis-scheduling stable so in order to be

protected against interruptions during implementation of project. Temporary protections (Gao 1995)increase duration of activities based on unreliability of amount of resources, which are used for activities. Resources that have possibility of failure or violation are called probable to violation resources. Protected duration of the activity includes main duration added to waiting duration of violation. Then basic scheduling is provided by problem solution with protected durations.

4.3 Reactive approach In Reactive scheduling, uncertainly are not given attention at creating basis scheduling but

when uncertainly occur, the approach tries to answer, correcting and re-optimize the basis scheduling. Generally, the approach’s main correction is on correcting and optimizing the basis scheduling if unanticipated events are occurred. The basis scheduling can be designed based on various strategies. On the other hand, answering to occurred changes can be based on very *Corresponding author (Mohammad Abdolshah). Tel: +98-231-4462198 E-mail address: [email protected]. 2014. International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies. Volume 5 No.4 ISSN 2228-9860 eISSN 1906-9642. Online Available at http://tuengr.com/V05/0253.pdf.

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simple techniques such as Right shift rule (Sadeh et al. 1993) that they are influenced because of the defect in resources or precedence relations, transferred to the right which means their implementation time are postponed, it’s obvious that the method is not a such good idea because it does not reschedule. The similar strategies are called schedule repair actions.

4.4 Fuzzy approach Fans of activity ambiguous express the probability distribution function of activities leads to

ambiguity and imprecise of estimation. The probability distribution function of an activity is ambiguous as long as information of its past, was not gained. A human expert should estimate the probability distribution function of an activity that often is non-recurring and exclusive.

4.5 Stochastic project approach Objective of stochastic project scheduling with resource constrained, is project scheduling

which is such that despite of activity duration uncertainly, precedence relations (Finish to start with zero lag) and renewable resource-constrained, minimizes make span. The studies on stochastic project scheduling are partly sporadic. Most of the studies are known as “stochastic project scheduling with resource-constrained” which are studied in next section.

5. Review of Solutions and Approaches of Resource-constrained Project Scheduling In order to review researches procedure and researches’ opportunities, all of the researches

are studied as two perspectives “ solution methods and approaches” in more than 200 papers of valid journals and after removing the similar articles, the chosen articles was studied and extracted their points and the results are shown by following tables. Tables 1 and 2 show the results of research about types of solution methods and approaches in RCPCP literature. There are brief explanations about important results of research in considerations column.

Table 1: RCPSP researches based on solution methods

Authors

Year

Solutions

Specifications Exact method

Not exact method

Heuristics Meta heuristics

Other

1. D.C. Paraskevopoulos et al.

2012 AILS, SAILS

Propos solution methodology, namely SAILS, operates on the event list and relies on a scatter search framework. The latter incorporates an Adaptive Iterated Local Search (AILS), as an improvement method, and integrates an event-list based solution combination method.

2. Chen Fang, Ling Wang

2012 SSGS SFLA Encode the virtual frog as the extended activity list (EAL) and decode it by the SFLA-specific serial schedule generation scheme (SSSGS) and To enhance the exploitation ability, a combined local search including permutation-based local search (PBLS) and forward–backward improvement (FBI) is performed.

3. Mohamed Haouari et al

2012 Dynamic programming, lower

Propose three classes of lower bounds that are based on the concept of Enhanced energetic reasoning


bounds

4. Ling Wangn, ChenFang

2012 SSGS, MFBI,

MPBLS

EDA In the EDA the individuals are encoded based on the activity-mode list (AML) and decoded by the multi-mode serial schedule generation scheme (MSSGS), and a novel probability model and an updating mechanism are proposed for well sampling the promising searching region.

5. Thomas S. Kyriakidis et al.

2012 MILP Present new mixed-integer linear programming models

6. KoorushZiarati etal.

2011 SSGS Bee algorithms

Proposed algorithms iteratively solve the RCPSP by utilizing intelligent behaviors of honeybees. Each algorithm has three main phases: initialization, update, and termination.

7. Shu-Shun Liu& Chang-Jung Wang

2011 CP A generic model is proposed to maximize the total profit of selected projects for construction and R&D departments given scheduling problems with various resource constraints during specified time intervals

8. FilipDeblaere et al.

2011 Simulation-based

Descent (SBD),

The procedure is basically a combination of four descent procedures that use simulation to evaluate the objective function

9. SiamakBaradaran et al.

2011 SSGS HMA Presents a hybrid met heuristic algorithm based on scatter search and path linking algorithms to solve the stochastic MRCPSP

10. Mohammad Ranjbar et al.

2011 Branch-and-

bound algorithm

Present a branch-and-bound algorithm in which the branching scheme starts from a graph representing a set of conjunctions In the search tree; each node is branched to two child nodes based on the two opposite directions of each undirected arc of disjunctions.

11. R. Čapek et al 2011 Linear programming model

IRSA A heuristic algorithm based on priority schedule construction with an un-scheduling step is proposed for the nested version of the problem and it is used to solve the case study of the wire harnesses production.

12. MariemTrojet et al.

2011 CP Provide a decision support framework under the constraints as a margin of cooperation/ negotiation with subcontractors

13. Ling Wang, Chen Fang

2011 SSGS Hybrid EDA

(HEDA)

Individuals are encoded based on the extended active list (EAL) and decoded by serial schedule generation scheme (SGS), a Forward–Backward iteration (FBI) and a permutation based local search method (PBLS) are incorporated into the EDA based search to enhance the exploitation ability

14. José Coelho, Mario Vanhoucke

2011 A novel meta-

heuristic

The algorithm splits the problem into a mode assignment step and a single mode project-scheduling step. The mode assignment step is solved using a fast and efficient SAT solver.

15. Ruey-Maw Chen

2011 SSGS JPSO The justification technique is combined with PSO as the proposed justification particle swarm optimization (JPSO), which includes other designed mechanisms.

16. Shanshan Wu et al.

2011 SSGS CBIIA The proposed CBIIA is based on the traits of an artificial immune system, chaotic generator and parallel mutation

17. Mahdi Mobini et al.

2011 SSGS AIA The proposed algorithm benefits from local search mechanisms as well as mechanism that enhances the diversity of the search directions

18. OumarKone et al.

2011 MILP Make a comparative study of several-mixed integer linear programming (MILP) formulations for resource-constrained project scheduling problems (RCPSPs).

19. LucioBianco& MassimilianoCaramia

2011 Lower bound

The lower bound is based on a relaxation of the resource constraints among independent activities and on a solution of the relaxed problem suitably represented by means of an AON acyclic network.

20. Agustín Barrios et al.

2011 DGA The heuristic is a two-phased genetic algorithm with different representation, fitness, crossover operator, etc., in each of them.

21. AnuragAgarw 2011 Neurogene A new hybrid of a neural network approach and the genetic


261



al et al. tic approach

algorithms approach

22. Francisco Ballestıín, RosaBlanco

2011 SSGS SPEA2, NSGA2 and PSA

Extensive computational results help decide which algorithms or techniques are the most promising for the problem.

23. FilipDeblaere et al.

2011 Branch-and-

bound

IDA TS Propose and evaluate a number of dedicated exact reactive scheduling procedures as well as a TABU search heuristic for repairing a disrupted schedule

24. TarunBhaskar et al.

2011 SPI Propose a non-recursive heuristic method based on priority rule for a new scheduling scheme and call it priority rule as Schedule Performance Index

25. GrzegorzWaligóra

2011 DCSGS Heuristic HUDD-PS

Different approaches to solving the continuous part of the problem were presented an exact approach requiring solving a convex mathematical programming problem, a heuristic approach to the continuous resource allocation problem (heuristic HUDD-PS), and the approach based on the continuous resource discretization.

26. José Fernando Gonçalves et al.

2011 FBI, SSGS

Genetic algorithm

Active schedules are constructed using a priority-rule heuristic in which the priorities of the activities are defined by the genetic algorithm. A forward-backward improvement procedure is applied to all solutions.

27. Vincent Van Peteghem, Mario Vanhoucke

2011 SSGS Scatter search

algorithm

Combination of improvement methods and the introduction of two local searches into one overall solution procedure leads to promising computational results

28. Reza Zamani 2011 SSGS A hybrid decomposi

tion procedure

The procedure finds an initial schedule for the project, and refines it through a decomposition process, To achieve further reduction, the refined schedule is over-refined by a genetic algorithm

29. Olivier Lambrechts et al.

2011 Time buffering using the

STC

Suggest to either implement time buffering based on the first surrogate objective function or using the STC heuristic

30. BehzadAshtiani et al.

2011 SSGS, local-search

A two-phase local-search procedure is developed to produce high-quality pre-processor policies for SRCPSP instance, first phase is devoted to finding good priority lists

31. Francisco Ballestín et al.

2011 SSGS, evolutiona

ry algorithm

Works on a population consisting of several distance-order-preserving activity lists representing feasible or infeasible schedules. The algorithm uses the conglomerate-based crossover operator

32. Jie Zhu et al. 2011 Genetic algorithm

During the genetic process of the proposed GA, an offspring generator was introduced to generate a feasible activity list from parent chromosomes

33. Mohammad Jaberi

2011 SSGS Potts-MFA

A Potts mean field feedback artificial neural network is designed and integrated into the scheduling scheme so as to automatically select the suitable activity for each stage of project scheduling

34. Hong Zhang,Feng Xing

2010 PSO FLC Present a fuzzy-multi-objective particle swarm optimization to solve the fuzzy TCQT problem. The time, cost and quality are described by fuzzy numbers and a fuzzy multi-attribute utility methodology incorporated with constrained fuzzy arithmetic operations is adopted to evaluate the selected construction methods

35. E. Klerides, E. Hadjiconstantinou

2010 Two-stage stochastic

integer programm

ing

Propose a path-based two-stage stochastic integer programming approach in which the execution modes are determined in the first stage while the second stage performs activity scheduling according to the realizations of activity durations

36. Qi Hao et al. 2010 A dynamic algorithm

A dynamic algorithm based on partial task networks ,practical heuristics for conflict detection, project prioritization and conflict resolution

37. Svio B. Rodrigues, Denise S. Yamashita

2010 MMBA algorithm

The new algorithm consists of a hybrid method where an initial feasible solution is found heuristically

38. Sonda Elloumi, Philippe

2010 A hybrid rank-based evolutiona

Introduce clustering algorithms to compute densities. In this way enforce that neighbor solutions belong to the same cluster and are assigned the same density.


Fortemps ry algorithm

39. AnisKooli et al.

2010 Integer programm

ing

New feasibility tests for the energetic reasoning are introduced based on new integer programming (IP) formulations.

40. Jairo R. Montoya-Torres et al.

2010 SSGS, PSGS

genetic algorithm

Propose an alternative representation of the chromosomes using a multi-array object-oriented model in order to take advantage of programming features in most common languages for the design of decision support systems

41. SiamakBaradaran et al.

2010 SSGS, PSGS

A hybrid scatter search

The path re-linking algorithm and two operators like crossover and prominent permutation-based are applied to solve the problem

42. Moslem Shahsavar et al.

2010 Genetic algorithm

Genetic algorithm (GA) is designed using a new three-stage process that utilizes design of experiments and response surface methodology.

43. C.U. Fündeling, N. Trautmann

2010 A novel method of

SGS

Present a priority-rule method based on a novel schedule-generation scheme and a consistency test for efficient scheduling of individual activities that iteratively determines a feasible resource-usage profile for each activity

44. Ruey-Maw Chen et al.

2010 A novel PSO

The delay local search enables some activities delayed and altering the decided start processing time. The bidirectional scheduling rule which combines forward and backward scheduling to expand the searching area in the solution space for obtaining potential optimal solution.

45. Wang Chen et al.

2010 SSGS ACOSS Algorithm combines a local search strategy, ant colony optimization (ACO), and a scatter search (SS) in an iterative process

46. Vincent Van Peteghem, Mario Vanhoucke

2010 SSGS GA Apply a bi-population genetic algorithm, which makes use of two separate populations and extend the serial schedule generation scheme by introducing a mode improvement procedure.


2010 Integer programm

ing

Propose a path-based two-stage stochastic integer programming approach in which the execution modes are determined in the first stage while the second stage performs activity scheduling according to the realizations of activity durations

48. Andrei Horbach

2010 Lower bounds

Solver is lightweight and shows good performance both in finding feasible solutions and in proving lower bounds

49. Angela H. L. Chen, Chiuh-Cheng Chyu

2010 Branch-and-

bound

The two-phase hybrid

metaheuristic

Using a branch-and-bound algorithm to solve the mode assignment problem in the first phase; then, by transforming a multi-mode case into a single-mode problem, the second phase was activated and the memetic algorithm was applied to achieve good quality solutions

50. WANG Hong et al.

2010 SSGS, PSGS,

FBI

GA Algorithm employs a standardized random key (SRK) vector representation with an additional gene that determines whether the serial or parallel schedule generation scheme (SGS) is to be used as the decoding procedure. The iterative forward-backward improvement as the local search procedure is applied upon all generated solutions

51. Reza Zamani 2010 Parallel complete anytime

procedure

Procedure finds a sequence of solutions in which every solution improves the previous one. To accelerate the convergence of the sequence to the optimal solution, the procedure simultaneously works in the forward and backward directions

52. JiupingXu&Zhe Zhang

2010 Hybrid genetic

algorithm

FLC Choose the hybrid genetic algorithm (HGA), and apply fuzzy logic control (FLC) to hybrid genetic algorithm (FLC-HGA) for enhancing the optimization quality and stability

53. Isabel Correia et al.

2010 Upper bound

A mixed-integer linear programming formulation, proposes a two-phase heuristic procedure for obtaining such bound. In the first phase, a feasible schedule is constructed. In the second phase, an attempt is made to improve this schedule by means of a local search procedure.

54. Wang Xianggang1 & Huang Wei

2010 Hybrid intelligent algorithm

Hybrid intelligent algorithm integrated by genetic algorithm and fuzzy simulation is designed to solve the above two fuzzy programming models.


263



55. H. R. Yoosefzadeh et al.

2010 PSGS Priority Rules

Compared the performance of forward, backward, bidirectional and tri-directional planning schemes in the context of different priority rules, The result obtained by each combination is an upper bound (UB) on the optimal project duration

56. Angelo Oddi et al.

2010 Different flattening algorithms within the ifs meta-heuristic strategy

Iterative flattening search (ifs) is a meta-heuristic strategy for solving multi-capacity scheduling problems. Given an initial solution, ifs iteratively applies: a relaxation-step, and a flattening-step

57. Doreen Krüger& Armin Scholl

2010 Mixed-integer model

At first develop a framework for considering resource transfers in single- and multi-project environments. Afterwards, define the multi-project scheduling problem with transfer times (RCMPPTT) and formulate it in a basic and an extended version as integer linear programs Eventually, it is supplemented for the first time by cost considerations

58. YuryNikulin& Andreas Drexl

2010 Pareto Simulated Annealing

A multi-criteria meta-heuristic, in order to get a representative approximation of the Pareto front

59. Tyson R. Browning &Ali A. Yassine

2010 A random generator

Present the first multi-network problem generator, The generator produces “near-strongly random” networks quickly, and can produce increasingly more strongly random networks at greater computational expense. Then identify a tradeoff between the degree of randomness and computational time

60. Fawaz S. Al-Anzi et al.

2010 Lower bound

A lower bound that uses a linear programming scheme for the RCPSP.

61. M. Ranjbar& F. Kianfar

2010 SSGS, a local

search

GA Developed a linear model for the problem, an enumeration procedure for generation of feasible work problems and a meta-heuristic, based on the Genetic Algorithm (GA), for solving the problem. Also developed a local search incorporated with GA to improve the solutions' quality

62. N. Damak et al.

2009 Differential evolution

(DE) algorithm.

Focus on the performance of this algorithm to solve the problem within small time per activity.

63. PengWuliang, Wang Chengen

2009 Improved genetic

algorithm

According to the characteristics of the proposed problem, an improved genetic algorithm was presented

64. Liang Yan et al.

2009 New heuristic approach

Combining the RCPSP model with the five heuristic, By comparing with those generated by the manual decision-making method, the results generated by heuristic algorithm indicate high efficiency

65. Po-Han Chen, Seyed Mohsen Shahandashti

2009 Hybrid of GA-SA

First attempts to use meta-heuristics and non-traditional techniques, can be seen that GASA Hybrid has better performance than GA, SA, MSA, and some most popular heuristic methods

66. Po-Han Chen,HaijieWeng

2009 Two-phase GA (genetic

algorithm)

The developed two-phase GA model works well. With further development to allow for multiple resource types, the two phase GA model could be generalized and applied to all sorts of resource-constrained project scheduling problems, including interruption and overlap of activities

67. VikramTiwari et al.

2009 IP Formulate the problem with a rework, quality-enhancing component and solve the resulting problem using commercial optimization procedures.

68. Jiaqiong Chen, Ronald G. Askin

2009 MIP Two versions of the Mixed Integer Program (MIP)

69. Mohammad Ranjbar et al.

2009 SSGS A hybrid scatter search

Using path re-linking methodology as a solution combination method.

70. Antonio Lova et al.

2009 SSGS, PSGS

a hybrid Genetic

Algorithm (MM-HGA)

A new parameter has been designed and its efficiency stated. In the evolution process characteristic of the GAs, fitness function plays a crucial role


71. J.J.M. Mendes et al.

2009 A random key based

genetic algorithm

The schedule is constructed using a heuristic priority rule in which the priorities of the activities are defined by the genetic algorithm.

72. Kuo-Ching Ying et al.

2009 A hybrid–directional planning scheme

To evaluate the effectiveness of the proposed scheme, different planning directions are incorporated into some meta-heuristics, including GA, SA, and TS

73. WU Yu et al. 2009 Timed colored Petri net (TCPN)

Firstly a novel mapping mechanism between traditional network diagram such as CPM (critical path method)/PERT (program evaluation and review technique) and TCPN was presented

74. JörgHomberger

2011 CMAS Multiple solutions consists of several self-interested schedule agents, each of which plans a single project decent rally and autonomously.

75. C.C. Chyu& Z.J. Chen

2009 Several variable

neighborhood search (VNS)algo

rithms

Developed by using insertion move and two swap to generate various neighborhood structures, and making use of the well-known backward–forward scheduling, a proposed future profit priority rule, or a short-term VNS as the local refinement scheme (D-VNS).

76. M. D. Mahdi Mobini et al.

2009 SSGS, PSGS

Enhanced scatter search

Decode to the solutions using both serial and parallel SGS and serial-SGS was used during the iterations of the algorithm. In the proposed ESS, three operators were used to generate new solutions from existing solutions in the reference set

77. Christian Artigues& Cyril Briand

2009 A new polynomial algorithm

As a basic search framework For reinsertion neighborhoods

78. Shu-Shun Liu,Chang-Jung Wang

2008 CP Presented model, constructed by Constraint Programming (CP), considers resource usage and cash flow in project scheduling to fulfill management requirements.

79. Nai-Hsin Pan et al.

2008 An improved TS model

Develop an improved TS model by modifying the way of finding a starting solution instead of traditional TS algorithm, minimum moment algorithm (MMA)

80. Stijn Van de Vonder et al.

2008 PSGS, RFDFF, VADE,

STC

Multiple efficient heuristic and meta-heuristic procedures are proposed to allocate buffers throughout the schedule

81. Francisco Ballestı´n et al.

2008 SSGS, DJGA,

1_DJGA

show how three basic elements of many heuristics for the RCPSP – codification, serial SGS and double justification – can be adapted to deal with interruption

82. R. Alvarez-Valdes et al.

2008 Several heuristic

algorithms

Procedures. Heuristic algorithms based on GRASP and Path re-linking are then developed and tested on existing test instances

83. J.F. Gonçalves et al.

2008 SSGS GA Schedules are constructed using a heuristic that builds parameterized active schedules based on priorities, delay times, and release dates defined by the genetic algorithm

84. Hédi Chtourou& Mohamed Haouari

2008 Two-stage-

priority-rule-based

The first stage solves the RCPSP for minimizing the makespan only using a priority-rule-based heuristic, namely an enhanced multi-pass random-biased serial schedule generation scheme. Then similarly solved for maximizing the schedule robustness while considering the makespan obtained in the first stage as an acceptance threshold.

85. Haitao Li, Keith Womer

2008 Constraint programm

ing

A constraint programming (CP) based solution approach is proposed and implemented in one case study

86. LuongDuc Long, ArioOhsato

2008 Developed a

procedure (named

P1)

The proposed method is useful for both project planning and execution which is well known priority heuristic rules and standard genetic algorithm

87. Mohammad Ranjbar

2008 a new heuristic algorithm

Proposes a new heuristic algorithm for this problem based on filter-and-fan method incorporated with a local search, exploring in the defined neighborhood space


265



88. Marek Mika et al.

2008 SSGS TS An application of a local search meta-heuristic TABU search for the considered problem has been described

89. Mario Vanhoucke

2008 Branch-and-

bound

First aim at the construction of efficient meta-heuristic solution procedures to solve the PRCPSP-FT and the PDTRTP-FT where set-up times are incorporated between pre-emptive sub-activities, Second try to extend this approach to a flexible activity assumptions problem setting

90. Shih-Tang Lo et al.

2008 ant colony optimization (ACO)

Present a modified ACO approach named DDACS for a multi-constraint multiprocessor scheduling problem The proposed DDACS algorithm modifies the latest starting time of each job in the dynamic rule for each iteration

91. Vicente Valls et al.

2008 SSGS Hybrid Genetic

Algorithm (HGA)

HGA introduces several changes in the GA paradigm: a crossover operator specific for the RCPSP; a local improvement operator that is applied to all generated schedules a new way to select the parents to be combined; and a two-phase strategy by which the second phase re-starts the evolution from a neighbor’s population of the best schedule found in the first phase.

92. L.-E. Drezet, J.C. Billaut

2008 MILP formulatio

n

Two-phase

heuristic algorithm

The first phase is a greedy algorithm, whose solution is used in the second phase as an initial solution for a TABU search algorithm

93. Mario Vanhoucke, Dieter Debels

2008 Branch-and-

bound

Present adapted lower bound and upper bound calculations for the PDTRTP-FT.

94. B. Jarboui et al.

2008 Combinatorial PSO (CPSO)

algorithm

CPSO algorithm outperforms the simulated annealing algorithm and it is close to the PSO algorithm. Also used a local search method to optimize the sequence associated to each assignment.

95. Sanjay Kumar Shukla et al.

2008 SSGS

Adaptive sample-

sort simulated annealing

FLC Propose a parallel intelligent search technique named the fuzzy based adaptive sample-sort simulated annealing (FASSA) heuristic. The basic ingredients of the proposed heuristic are the serial schedule generation scheme (SGS), sample sort simulated annealing (SSA), and the fuzzy logic controller (FLC).

96. Olivier Lambrechts et al.

2008 SSGS Time slack-based

techniques, TS

Develop an approach for inserting explicit idle time into the project schedule in order to protect it as well as possible from disruptions caused by resource un-availabilities.

97. Olivier Liess& Philippe Michelon

2008 Constraint programm

ing

Classical Constraint Programming approach for the (RCPSP) except that the timetable algorithm is not considered.

98. A. A. Lazarev& E. R. Gafarov

2008 Branch-and-

bound

Prove that method like branch-and-bound (branch & bounds, Constraint Programming, and so on) with the lower estimate LBM be ineffective.

99. MajidSabzehparvar& S. Mohammad Seyed-Hosseini

2008 Linear mixed integer

programming

Time horizon can be continuous in this model thus dealing with different processing time units

100. Jean Damay et al.

2007 Linear programm

ing

A time-indexed linear formulation of the non-preemptive version of the RCPSP involving these feasible subsets

101. ShahramShadrokh, FereydoonKianfar

2007 GA 690 problems are solved and their optimal solutions are used for the performance tests of the genetic algorithm

102. Mohammad R. Ranjbar, FereydoonKianfar

2007 SSGS Ameta-heuristic algorithm

Based on the genetic algorithm and a new method based on the resource utilization ratio is developed for generation of crossover points and also a local search method is incorporated with the algorithm

103. JirachaiBuddhakulsomsi, David S. Kim

2007 SSGS, Priority

rule-based

Both deterministic multi-pass and stochastic multi-pass heuristics have been constructed

104. Stijn Van de Vonder et al.

2007 SSGS, PSGS,

weighted-

Present a sampling procedure that combines the schemes with multiple priority lists. Also describe a heuristic for the weighted earliness–tardiness problem


earliness tardiness heuristic

105. Jacques Carlier& Emmanuel Néron

2007 Enumeration

algorithm

Propose an explicit enumeration of the redundant resources and a characterization of the non-dominated ones

106. M. Rabbani et al.

2007 A new heuristic algorithm

In order to prevent creating a lower bound for the mean project completion time, the most critical chain is determined and its standard deviation is added to project completion time as the project buffer

107. VéroniqueBouffard& Jacques A. Ferland

2007 Improving simulated annealing

with variable

neighborhood search

Consistent with the fact that the simulated annealing approach performs better than the TABU search approach for RCPSP Furthermore, the performance of the simulated annealing method can be improved with a variable neighborhood search approach

108. RinaAgarwal et al.

2007 Artificial immune system

The performance of the proposed AIS algorithm on test problem, reported in literature is found to be superior, when compared with GA, fuzzy-GA, LFT, GRU, SIO, MINSLK, RSM, RAN, and MJP

109. Lin-Yu Tseng, Shih-Chieh Chen

2006 A hybrid meta

heuristic ANGEL

ANGEL combines ant colony optimization (ACO), genetic algorithm (GA) and local search strategy. Also proposes an efficient local search procedure that is applied to yield a better solution when ACO or GA obtains a solution. A final search is applied upon the termination of ACO and GA

110. Amir Azaron, Reza Tavakkoli-Moghaddam

2006 Non-linear

programming

The dynamic PERT network, representing as a network of queues, was transformed into an equivalent classical PERT network

111. Luciano LessaLorenzoni et al.

2006 An evolutiona

ry algorithm

An algorithm based on differential evolution algorithm was selected to serve as a solution procedure.

112. Dieter Debels et al.

2006 SSGS A new meta-

heuristic(EM)

The procedure is a population-based evolutionary method that combines elements from scatter search, a generic population-based evolutionary search method, and from a recently introduced heuristic method for the optimization of unconstrained continuous functions based on an analogy with electromagnetism theory

113. Hong Zhang et al.

2006 PSGS Particle swarm

optimization (PSO)

A PSO-based method including its corresponding framework is proposed for solving the RCPSB

114. John-Paris Pantouvakis, Odysseus G. Manoliadis

2006 a heuristic method

A heuristic method is developed based on traditional CPM scheduling Calculations and leveling algorithms

115. Guidong Zhu et al.

2006 A branch and cut

Based on the integer linear programming (ILP) formulation of the problem

116. I-Tung Yang, Chi-Yi Chang

2005 Linear programm

ing

Present a chance-constrained programming model, derive its deterministic equivalent, and solve the equivalent by classical linear programming techniques., Model verification is performed by Monte Carlo simulations

117. Marek Mika et al.

2005 SSGS Simulated annealing

and TABU search

Applications of two local search meta-heuristics

118. M.A. Al-Fawzan, Mohamed Haouari

2005 SSGS TABU search

algorithm

Develop a TABU search algorithm in order to generate an approximate set of efficient solutions

119. KwanWoo Kim

2005 SSGS Hybrid genetic

FLC The proposed new approach is based on the design of genetic operators with fuzzy logic controller (FLC) through


267



algorithm with fuzzy

logic controller

(FLC-HGA)

initializing the revised serial method which outperforms the non-preemptive scheduling with precedence and resources constraints

120. Tamás Kis

2005 a branch-and-cut

algorithm

Formalize the problem by means of a mixed integer-linear program, prove that feasible solution existence is NP-complete in the strong sense and propose a branch-and-cut algorithm for finding optimal solutions

121. Sophie Demassey& Chiristian Artigues

2005 Lower bound, linear

programming

A heuristic method

Propose a cooperation method between constraint programming and integer programming to compute lower bounds for the RCPSP.

122. Krzysztof Fleszar, Khalil S. Hindi

2004 SSGS, variable

neighborhood

search(VNS)

In addition to the use of VNS to explore the solution space, the effectiveness of the scheme is due to progressively reducing the solution space by repeatedly improving both lower and upper bounds, as well as by discovering additional valid precedence to augment the existing set.

123. Juite Wang 2004 SSGS Genetic algorithm

Adapt a Branch-and-Bound algorithm for resource-constrained project scheduling by Bell and Park (1990) to the fuzzy case. And propose GA approach can obtain the robust schedule with acceptable performance

124. I.E. Diakoulakis et al.

2004 Evolution Strategies

(ES)

Under two discrete solution encodings; one works on vectors of priority values and the other is based on convex combinations of priority rules

125. Reza Zamani 2004 Time window

SA Procedure consists of a SA component and a time-windowing process. The SA component generates a base schedule and the time-windowing process improves the base. The combination of three factors contributes to the efficiency of the simulated annealing component

126. ChristophMellentien

2004 A relaxation-

based beam-search

solution

Present a relaxation-based beam-search solution heuristic. Exploiting a duality relationship between temporal scheduling and min-cost network flow problems solves the relaxations.

127. Vicente Valls & Francisco Ballestín

2004 SSGS, PSGS

Convex Search,

Homogeneous

Interval Algorithm

(back ward,

forward)

Scatter search

Procedure incorporates various strategies for generating and evolving a population of schedules. It is the result of combining four innovative basic procedures

128. Philippe Baptiste & Sophie Demassey

2004 Tight LP bounds

14 more lower bounds are improved in an average CPU time of 284.6 seconds

129. Mireille Palpant et al.

2004 SSGS LSSPER Present the Local Search with Sub-Problem Exact Resolution (LSSPER) method based on large neighborhood search for solving the problem

130. A. LIM et al. 2004 A hybrid framework

This hybrid framework has a two-level structure. TS and GA heuristic searches were used in the high level components of algorithms. For the low level components, a CP-based iterative randomized method and a Minimal Critical Set-based method were used to resolve temporal and resource conflicts. The four combinations of these – Tabu_CP, Tabu_MCS, GA_CP, GA_MCS – were tested on two sets of real test data

131. Christian Artigues et al.

2003 PSGS, a new

Show that such an algorithm is of great interest for robust rescheduling in a dynamic environment


polynomial insertion algorithm

132. Vicente Valls et al.

2003 SSGS A new meta

heuristic algorithm CARA,

Non-standard implementation of fundamental concepts of TABU search without explicitly using memory structures embedded in a population-based framework, makes use of the TO representation of schedules

133. J. Carlier& E. Néron

2003 Linear lower

bounds (LLB)

First application that we present is a general linear programming scheme for computing a makespan lower bound. The second application consists in associating redundant resources with LLB

134. DimitriGolenko-Ginzburg et al.

2003 RCGPS algorithm

Algorithm can be used for CAAN models which cover a broad spectrum of alternative stochastic networks

135. Roland Heilmann

2003 Branch-and-

bound

The solution method is a depth-first search based branch-and-bound procedure. It makes use of a branching strategy where the branching rule is selected dynamically. The solution approach is an integration approach where the modes and start times are determined simultaneously.

136. Kwan Woo Kim et al.

2003 SSGS Hybrid genetic

algorithm (HGA)

with fuzzy logic

controller (FLC)

FLC Based on the design of genetic operators with FLC and the initialization with the serial method, to find optimal or near-optimal initial solutions which has been shown superior for large-scale RCPSP

137. M Kamrul Ahsan& De-Bi Tsao

2003 bi-criteria search

strategy of a heuristic learning

Formulate a state-space representation of a heuristic search algorithm with a bi-criteria partial schedule selection technique. The heuristic solves problems in two phases. Also propose a variable weighting technique based on initial problem complexity measures.

138. J Alcaraz et al. 2003 GA Before the genetic algorithm itself is started, apply a preprocessing procedure over the project data, in order to reduce the search space.(to reduce the volume of the data and speed up the execution of their algorithm for this problem.)

139. Chiu-Chi Wei et al.

2002 Enhanced TOC

method

The enhanced TOC project scheduling technique determines the lower bound of the project length by using the combination of the existing heuristic algorithms, used to conduct the activity duration cut and establish project buffer, feeding buffer and resource buffer

140. AmedeoCesta& Angelo Oddi

2002 A heuristic

algorithm(ISES)

Use of an iterative sampling procedure which relies, on a constraint satisfaction problem solving (CSP) search procedure

141. A Sprecher 2002 a new heuristic

The strategy combines elements of exact and heuristic solution procedures. It relies on decomposition of a problem into sub-problems, near optimal solution of the sub-problems, and concatenation of the sub-problem solutions. The algorithm significantly outperforms the truncated exact branch-and bound algorithm on larger instances.

142. Mario Vanhouck et al.

2001 Branch-and-

bound

Introduce a depth-first branch-and-bound algorithm which makes use of extra precedence relations to resolve resource conflicts and relies on a fast recursive search algorithm for the unconstrained weighted earliness–tardiness problem to compute lower bounds

143. Birger Franck et al.

2001 Branch-and-

bound

SSGS, heuristic

procedures

Propose several truncated branch-and-bound techniques, priority-rule methods, and schedule-improvement procedures of types TABU search and genetic algorithm

144. GunduzUlusoy et al.

2001 Genetic algorithm

(GA)

Use a special crossover operator that can exploit the multi-component nature of the problem.

145. Sönke 2001 SSGS Genetic Extending the genetic algorithm framework by local search


269



Hartmann Algorithm concepts used two local search methods. One was designed to deal with the feasibility problem of the MRCPSP, while the other was used to improve the schedules found by the GA

146. A. Kimms 2001 Tight Upper

Bounds

Lagrangian

relaxation

Derive tight upper bounds on the basis of a Lagrangian relaxation of the resource constraints And also use this approach as a basis for a heuristic

147. J. Prashant Reddy et al.

2001 Genetic-algorithm

Describe Petri-net-aided software including genetic-algorithm-based search and heuristics

148. Antonio Lova&PilarTormos

2001 SSGS, PSGS, New

heuristics

Analyze the effect of the schedule generation schemes – serial or parallel and priority rules. Also New heuristics –based on priority rules with a two-phase approach

149. Joanna Jozefowska et al.

2001 SSGS A new simulated annealing algorithm

Two versions of the simulated annealing approach are discussed: SA without penalty function and SA with penalty function

150. PilarTormos& Antonio Lova

2001 SSGS, PSGS, hybrid

multi-pass method

Technique is a hybrid multi-pass method that combines random sampling procedures with a backward–forward also the algorithm includes as a determinant characteristic the alternative use of the serial and parallel schedule generation schemes in such a way that it benefits from the properties provided for both of them.

151. Roland Heilmann

2001 Multi–pass

priority–rule

method

The heuristic is a multi–pass priority–rule method with back planning which is based on an integration approach and embedded in random sampling

152. Gary Knotts et al.

2000 Eight agent-based

algorithms

Develop and experimentally evaluate eight agent-based algorithms, algorithms differ in the priority rules used to control agent access to resources

153. ChristophSchwindt & Norbert Trautmann

2000 Branch–and-

bound algorithm

Solve to feasibility by a simple batching heuristic and the subsequent solution of the corresponding batch scheduling problem by a truncated version of the branch–and–bound algorithm within one minute

154. Erik Demeulemeester et al.

2000 Branch–and-

bound algorithm

Present a depth-first branch-and-bound procedure for the discrete time/resource trade-off problem in project networks (DTRTP)

155. Ulrich Dorndrof et al.

2000 Time-oriented branch-

and-bound

Describe a time-oriented branch and bound algorithm that uses constraint propagation techniques

156. Arno Sprecher 2000 Branch-and-

bound

The main purpose of this paper is direct focus to a branch-and-bound concept

157. Tam P. W. M. & E. Palaneeswaran

1999 A new heuristic method

Note first outlines the suitability of ranked positional weight method (RPWM), a heuristic resource scheduling method, to construction project scheduling. It then focuses on a new heuristic technique, the enhanced positional weight (EPWM), which is an improved version of the RPWM. Some interesting comparisons between the results given by Primavera, Microsoft Project, RPWM, and EPWM are also presented

158. Shue Li-Yen,RezaZamani

1999 An intelligent

search method

Present an admissible heuristic search algorithm SLA, and an implementation method for solving the RCPSP, this algorithm is characterized by the complete heuristic learning process: state selection, heuristic learning, and search path review

159. Paul R. Thomas &Said Salhi

1998 Tabu Search

Approach(PSTSM)

Deal with a number of TABU search heuristic concepts in order to construct a method for this combinatorial problem, namely the PSTSM heuristic

160. Abel A.Fernandez

1998 Alternative

simulation

Introduces a multi-period stochasticing programming based model of the project scheduling problem


algorithm 161. Aristide,

Mingozzi et al.

1998 Branch and

bounds, A new 0-1 linear

programming

formulation, a tree search

algorithm

Relaxation heuristic method

Based on a new mathematical formulation which is used to derive 5 new lower bounds and also described a new tree search algorithm based on this exact formulation that uses the new bounds

162. Dan Zhu &RemaPadman

1997 Artificial neural

networks

Apply neural networks to induce the relationship between project parameters and heuristic performance to guide the selection under different project environments

163. Rainer Kolisch& Andreas Drexl

1997 a new local

search

Propose a new local search method that first tries to and a feasible solution and secondly performs a single-neighborhood search on the set of feasible mode assignments.

164. Arno Sprecher et al.

1997 a new branch

and bound algorithm

Present a new procedure which is a considerable generalization of the branch and-bound algorithm proposed by Demeulemeester and Herroelen

165. Kedar S. Naphade et al.

1997 Two distinctly different problem

space search

procedures

Embed a fast base heuristic (for instance, a dispatching rule) within a search procedure, then showing comparable performance to the branch-and-bound algorithm.

166. Moizuddin, Mohammed&Selim, S. Z.

1997 TS The algorithm uses the priority space for generating neighbors. it also employed uses a short-term memory component. to optimize the TS parameters that developed are 3k factorial design.

167. Erik Demeulemeester, Willy S L Herroelen

1997 A new branch

and bound algorithm

Describe a new depth-first branch-and-bound algorithm(GDH-PROCEDURE)

168. Kum-Khiong, yang

1996 MINSLAK, CPR,

FCFS

SA A total of one scheduling and three heuristic dispatching rules that these planning rules are used to specify the priority of each activity in a project b ranking the precedence-feasible activities on an activity priority list.

169. OyaIcmeli, S SelcukErenguc

1996 A branch and bound procedure

The bounds in the branch and bound procedure are computed by solving payment-scheduling problem that can be formulated as linear programs and by that are well solvable.

170. F.Brian Talbot 1982 Integer program-

ings

A heuristic solution

A two stages solution methodology is developed which builds upon idea presented earlier. Stage one defines the problem as a compact integer-programming problem, stage two searches for the optimal solution using an implicit enumeration scheme that systemically improves upon generated heuristic solutions.

171. Jan Weglarz 1981 A priority analyses

The properties of optimal schedules are given for strictly, concave and convex activity models.

172. Dale F Cooper 1976 PSGS, Tow

classes of heuristic

procedure

Assess the effects of the heuristic method, the project characteristics and the priority rules

173. Arne Thesen 1976 A new heuristic method

Extend the fields of heuristic algorithms for RCPSP. a sub optimizing resource allocation algorithm is employed, A new hybrid heuristic urgency factor is introduced and finally a systematic approach to the evaluation of the such algorithm is presented

174. E. W. Davis& G. E. Heidorn

1971 A dynamic

programm

A dynamic programming approach that is a form of bounded enumeration. is presented to perform the shortest-path determination during construction of the a-network


271



ing approach

175. A.Thomas Mason, Colin L Moodie

1971 A branch and bound procedure,

A heuristic method

Cost bounding procedures are augmented by dominance relationships presented as theorems. Initial feasible schedules are generated using a heuristic scheduling rule. Both heuristics rule and the branch and bound algorithm have been programmed for the computer

176. Jerome D.Wiest

1967 A heuristic method

Describe a computer model capable of scheduling single or multiple projects within theirs constraints

In table 2 the approaches on RCPSP subject are categorized in different level. as seen most of the approaches are definite and discrete which is a big question that why researchers did not intend to work on other field.

Table 2: Approaches Categories

Authors

Year

Approaches Number of approaches

Det. Stochastic Discrete Integrated

Reactive Proactive Stochastic Fuzzy

1. D.C. Paraskevopoulos et al. 2012

2. Chen Fang, Ling Wang 2012

3. Mohamed Haouari et al 2012

4. Ling Wangn, ChenFang 2012

5. Thomas S. Kyriakidis et al. 2012

6. Koorush Ziarati et al. 2011

7. Shu-Shun Liu, Chang-Jung Wang

2011

8. FilipDeblaere et al. 2011

9. SiamakBaradaran et al. 2011

10. Mohammad Ranjbar et al. 2011

11. R. Čapek et al. 2011

12. MariemTrojet et al. 2011

13. Ling Wang, Chen Fang 2011

14. José Coelho, Mario Vanhoucke

2011

15. Ruey-Maw Chen 2011

16. Shanshan Wu et al. 2011

17. Mahdi Mobini et al. 2011

18. OumarKone et al. 2011

19. LucioBianco, MassimilianoCaramia

2011

20. Agustín Barrios et al. 2011

21. AnuragAgarwal et al. 2011

22. Francisco Ballestıín, Rosa Blanco

2011

23. FilipDeblaere et al. 2011


24. TarunBhaskar et al. 2011

25. GrzegorzWaligóra 2011

26. José Fernando Gonçalves et al.

2011

27. Vincent Van Peteghem,Mario Vanhoucke

2011

28. Reza Zamani 2011

29. Olivier Lambrechts et al. 2011

30. BehzadAshtiani et al. 2011

31. Francisco Ballestín et al. 2011

32. Jie Zhu et al. 2011

33. Mohammad Jaberi 2011

34. Hong Zhang,Feng Xing 2010


2010

36. Qi Hao et al. 2010

37. Svio B. Rodrigues, Denise S. Yamashita

2010

38. SondaElloumi , Philippe Fortemps

2010

39. AnisKooli et al. 2010

40. Jairo R. Montoya-Torres et al.

2010

41. SiamakBaradaran et al. 2010

42. Moslem Shahsavar et al. 2010

43. C.U. Fündeling, N. Trautmann

2010

44. Ruey-Maw Chen et al. 2010

45. Wang Chen et al. 2010

46. Vincent Van Peteghem , Mario Vanhoucke

2010


2010

48. Andrei Horbach 2010

49. Angela H. L. Chen & Chiuh-Cheng Chyu

2010

50. Wang Hong et al. 2010


52. JiupingXu&Zhe Zhang 2010

53. Isabel Correia et al. 2010

54. Wang Xianggang& Huang Wei

2010

55. H. R. Yoosefzadeh et al. 2010


273



56. Angelo Oddi et al. 2010

57. Doreen Krüger&Armin Scholl

2010

58. YuryNikulin&Andreas Drexl

2010

59. Tyson R. Browning &Ali A. Yassine

2010

60. Fawaz S. Al-Anzi et al. 2010

61. M. Ranjbar& F. Kianfar 2010

62. N. Damak et al. 2009

63. PengWuliang, Wang Chengen

2009

64. Liang Yan et al. 2009

65. Po-Han Chen,Seyed Mohsen Shahandashti

2009

66. Po-Han Chen,HaijieWeng 2009

67. VikramTiwari et al. 2009

68. Jiaqiong Chen, Ronald G. Askin

2009

69. Mohammad Ranjbar et al. 2009

70. Antonio Lova et al. 2009

71. J.J.M. Mendes et al. 2009

72. Kuo-Ching Ying et al. 2009

73. Wu Yu et al. 2009

74. JörgHomberger 2011

75. C.C. Chyu&Z.J. Chen 2009

76. M. D. Mahdi Mobini et al. 2009

77. Christian Artigues& Cyril Briand

2009

78. Shu-Shun Liu,Chang-Jung Wang

2008

79. Nai-Hsin Pan et al. 2008

80. Stijn Van de Vonder et al. 2008

81. Francisco Ballestín et al. 2008

82. R. Alvarez-Valdes et al. 2008

83. J.F. Gonçalves et al. 2008

84. Hédi Chtourou & Mohamed Haouari

2008

85. Haitao Li, Keith Womer 2008 Supply chain configuration

problem (SCCP) under

resource constraints

86. LuongDuc Long, ArioOhsato

2008

87. Mohammad Ranjbar 2008

88. Marek Mika et al. 2008


89. Mario Vanhoucke 2008

90. Shih-Tang Lo et al. 2008

91. Vicente Valls et al. 2008

92. L.-E. Drezet, J.-C. Billaut 2008

93. Mario Vanhoucke, Dieter Debels

2008

94. B. Jarboui et al. 2008

95. Sanjay Kumar Shukla et al. 2008

96. Olivier Lambrechts et al. 2008

97. Olivier Liess&Philippe Michelon

2008

98. A. A. Lazarev& E. R. Gafarov

2008

99. MajidSabzehparvar& S. Mohammad Seyed-Hosseini

2008

100. Jean Damay et al. 2007

101. ShahramShadrokh, FereydoonKianfar

2007

102. Mohammad R. Ranjbar, FereydoonKianfar

2007

103. JirachaiBuddhakulsomsi, David S. Kim

2007

104. Stijn Van de Vonder et al. 2007

105. Jacques Carlier, Emmanuel Ne´ron

2007

106. M. Rabbani et al. 2007 RCPSP-TOC

107. VéroniqueBouffard&Jacques A. Ferland

2007

108. RinaAgarwal et al. 2007

109. Lin-Yu Tseng, Shih-Chieh Chen

2006

110. Amir Azaron, Reza Tavakkoli-Moghaddam

2006

111. Luciano LessaLorenzoni et al.

2006

112. Dieter Debels et al. 2006

113. Hong Zhang et al. 2006

114. John-Paris Pantouvakis, Odysseus G. Manoliadis

2006

115. Guidong Zhu et al. 2006

116. I-Tung Yang, Chi-Yi Chang

2005

117. Marek Mika et al. 2005

118. M.A. Al-Fawzan, Mohamed Haouari

2005

119. KwanWoo Kim 2005

120. Tamás Kis 2005


275



121. Sophie Demassey&Chiristian Artigues

2005

122. Krzysztof Fleszar, Khalil S. Hindi

2004

123. Juite Wang 2004

124. I.E. Diakoulakis et al. 2004


126. ChristophMellentien 2004

127. Vicente Valls & Francisco Ballestín

2004

128. Philippe Baptiste& Sophie Demassey

2004

129. Mireille Palpant et al. 2004

130. A. Lim et al. 2004

131. Christian Artigues et al. 2003

132. Vicente Valls et al. 2003

133. J. Carlier, E. N_eron 2003

134. DimitriGolenko-Ginzburg et al.

2003

135. Roland Heilmann 2003

136. Kwan Woo Kim et al. 2003

137. M Kamrul Ahsan & De-Bi Tsao

2003

138. J Alcaraz et al. 2003

139. Chiu-Chi Wei et al. 2002 RCPSP-TOC

140. Amedeo Cesta& Angelo Oddi

2002

141. A Sprecher 2002

142. Mario Vanhoucke et al. 2001

143. Birger Franck et al. 2001

144. Gunduz Ulusoy et al.

2001

145. Sönke Hartmann 2001

146. A. Kimms 2001

147. J. Prashant Reddy et al. 2001

148. Antonio Lova & Pilar Tormos

2001

149. Joanna Jozefowska et al. 2001

150. Pilar Tormos & Antonio Lova

2001

151. Roland Heilmann 2001

152. Gary Knotts et al. 2000

153. Christoph Schwindt & Norbert Trautmann

2000

154. Erik Demeulemeester et al. 2000


155. Ulrich Dorndrof et al. 2000

156. Arno Sprecher 2000

157. Tam P. W. M. & E. Palaneeswaran

1999

158. Shue Li-Yen,RezaZamani 1999

159. Paul R. Thomas & Said Salhi

1998

160. Abel A.Fernandez 1998

161. Aristide, Mingozzi et al. 1998

162. Dan Zhu&RemaPadman 1997

163. Rainer Kolisch & Andreas Drexl

1997

164. Arno Sprecher et al. 1997

165. Kedar S. Naphade et al. 1997

166. Moizuddin, Mohammed;Selim, Shokri Z

1997

167. Erik Demeulemeester, Willy S L Herroelen

1997

168. Kum-Khiong, yang 1996

169. Oya Icmeli & S. Selcuk Erenguc

1996

170. F.Brian Talbot 1982

171. Jan Weglarz 1981

172. Dale F Cooper 1976

173. Arne Thesen 1976

174. Davis, Edward W;Heidorn, George E

1971

175. A.Thomas Mason, Colin L Moodie

1971

176. Jerome D.Wiest 1967

6. Conclusion Every day, better usage of the organizational resources such as machinery, human resource

and materials are given more attentions. With existence of resource constraints, planning for achieving the goals of the contracts in projects, and at the top of them, time obligations, become more important. This paper described models and approaches in literature of project scheduling by considering resource constraints and the described models in literature that consist of more than 200 published articles in well known journals, are collected and provided in forms of a codified table. We tries to categorize models appropriately in this paper and surveys the proposed solutions for them by researches. By considering the increasing deployment of using planning and controlling project methods in organizations, factories and workshops such as powerhouse equipment construction projects and any kind of executive projects in various *Corresponding author (Mohammad Abdolshah). Tel: +98-231-4462198 E-mail address: [email protected]. 2014. International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies. Volume 5 No.4 ISSN 2228-9860 eISSN 1906-9642. Online Available at http://tuengr.com/V05/0253.pdf.

277



industries and totally, where ever there is usage of planning and controlling project, and by considering the diversity of organizations and factories, can identify the required model by considering the proposed criterions at beginning of this paper and researchers find the gaps in literature and try to fill them. We hope that the proposed solutions are reliable resources and references for gathering more information about different existence solutions in RCPSP literature.

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Comparison between Analytical Results and Response of the Laboratory-Scaled Truss Bridges under the Moving Car Load

Surachet Charnrit a, Weerayut Krahothong a, and Chaisak Pisitpaibool a*

a Department of Civil Engineering Faculty of Engineering, Thammasat University, THAILAND A R T I C L E I N F O A B S T RA C T Article history: Received 15 May 2014 Received in revised form 21 July 2014 Accepted 25 July 2014 Available online 29 July 2014 Keywords: Laboratory scaled model; Moving car load; Static loading; Unexpected truss behavior.

Two sets of the two traditional types of the laboratory-scale -parallel chorded truss bridges under the moving car loads are conducted. Both steel bars used to assemble the bridges and a miniradio-controlled kid-car used as the applied loads are selected from materials available in the market. The experimental programs address the unexpected rebound behavior of the vertical deflection of a truss model under the low speed of the moving car loads. This behavior, however, cannot be detected by the traditional and numerical analysis methods. The rebound behavior of the model may require further investigation.


1. Introduction A two-parallel chorded truss is commonly used as a bridge structure, which is built up as

the distance for joining two areas at the end supports. Difference of the geometric

arrangement of its diagonal members converts the applied loading into different manners of

the tensile or compressive internal forces causing a bend of the entire truss.A truss span

ranging from 9 m to 122 m is economically possible to be selected for forming a bridge

structure, although the greater span lengths have occasionally been used (Hibbeler, R. C.,

2009). Based on the response of the interaction between the bridge structures and their loads

applied, the truss behaviors have been experimentally and analytically investigated by

different researchers.


*Corresponding author (C.Pisitpaibool). Tel/Fax: +66-2-5643001 Ext.3102. E-mail address: [email protected]. 2014. International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies. Volume 5 No.4 ISSN 2228-9860 eISSN 1906-9642. Online available at http://tuengr.com/V05/0287.pdf.

287



Bacinskas, et al. (2013)employed the aid of full-scale static and dynamic testing to

explore the structural condition and the behaviour of the riveted of a historic narrow-gauge

railway steel truss bridge built in 1936. For assessment of bridge capacity, an analytical model

was developed from conducting the field load tests. Static and dynamic tests of the bridge

using two original engines were performed. Additionally dynamic tests using impulse

excitation were also investigated. Thestructural responses (stresses, static and dynamic

displacements, accelerations, mode shapes, corresponding resonant frequencies and modal

damping values) of the bridge superstructure were determined. Investigation has shown that

the bridge revealed sufficient capacity for safe operation.

Brunell and Kim (2013) investigated the performance of a steel truss bridges subjected to

local damage. The existence of local damage was detected by an indicator called the global

safety index of the system based on deflection characteristic. It was emphasized that the

development of a repair method capable to address the global redundancy of a damaged truss

bridge was required.

Cheng, B., Qian, G., and Sun, H., (2013), used the finite element method to analyze the

elastic and elasto-plastic behaviors of trusses consisting of the bowknot/conventional integral

joints. The results expressed that the secondary moments at the member ends and the

sectional maximum stresses of the un-shrunken segments of the truss were significantly

reduced by the section-shrinking of the member ends. Conversely, the vertical stiffness and

elastic stability of the bowknot truss were deteriorated comparing to the conventional one.

When the steel strength of the shrunken segments had been appropriately improved, the

ultimate bearing capacities of axially compressed shrunken members and of Warren trusses

with bowknot integral joints were as high as those of uniform members and of conventional

trusses, respectively.

The initial main purpose of this study was to set up the basic experimental program of the

prototype model to investigate the response of a bridge behavior under the moving load

condition. During the verification stage, it was found that the normal speed of the mini radio-

controlled kid-car (applied load) was too fast to detect by the dial gauge. The car was then

pulled forward with a very low speed. Due to the circumferential model condition, the

unexpected rebound behavior of the vertical deflection of a truss model was found. This

behavior is then become the point of interested in this study.

288 Surachet Charnrit, Weerayut Krahothong, and Chaisak Pisitpaibool

2. Experimental Study Works on the study of the experimental response of the laboratory-scaled truss bridge

under the moving car load were divided into three parts. The first part deals with how to

design the truss bridge models, which includes the geometric arrangement of its members and

organizing the material to fabricate the model by welding. The second and third parts concern

with load device and test procedure, respectively, obtaining from the moving car load.

2.1 Truss Bridge Model Design and Manufacture Two series of the Pratt and Warren types of the Pony truss bridge models were

experimental studied. A model was composed of two steel trusses laying in the vertical

planes along the two sides of the bridge. Each truss had the longitudinal parallel top and

bottom chords as shown in the Figure 1. The truss specimens were named as the Pt1, Wr1,

Pt2 and Wr2. The first two letters indicated its type while the last letter indicated the series

number. Each truss had a total span of 2.50 m and the horizontal dimension of each diagonal

member was 25 cm. The depths of the first and second series were 25 cm and 15 cm,

respectively.

Figure 1: Truss Bridge Models.

The steel bars used to assemble the bridges were intended to select from the smallest size of the materials available in the market. The longitudinal parallel top and bottom chords were made from the 4/8 tube bars, which inner and outer diameters were 18.9 mm and 21.7 mm, respectively. The vertical and diagonal members were the SD24-RB6 reinforcing steel,

25

25 cm

15 cm

10 @ 25 cm = 2.50 m

15 cm

Pt1

Wr1

Pt2

Wr2


289



whose diameter was 6 mm which was the smallest size of the commercial reinforcing steel. In order to stabilize the whole truss system, 6 bars of the SD24-RB6 reinforcing steel were used as the bracings placed at the bottom chords. The main structural assembly of the truss bridge model is shown in the Figure 2. The deck was made from the viva-board of 10 mm thickness.

Figure 2: Truss bridge models in the initially set-up the program.

2.2 Loading Device A mini radio-controlled kid-car was selected as the applied moving loads due to its

available in the market with the affordable budget. Various weights had been experimentally applied to the bridge truss models. However, Table 1 shows the car load distribution only for the two extreme cases, which are the minimum case when the car is empty and the maximum case when the car was loaded until the maximum capacity was reached. The maximum capacity used of the kid-car was 24.04 kg.

Table 1: Load distribution of the car model.

Empty car load (kg) Full load (kg)

Front wheels 5.79 12.42 Rear wheels 5.96 11.62 Total car load 11.75 24.04

2.3 Instrumentation and Test Procedure The experiment started with the first series of the Pratt and Warren types (Pt1 and Wr1).

In fact, in the second series it was intended to investigate the behavior of the other types (e.g.,


the Pratt or K-trusses) of the truss models. Basic types of instrumentation were used to

monitor the behavior during the tests. A small load cell was placed under the supported

bracing which located at one end of the longitudinal bottom chord. Strain gauges were placed

at some middle bars to measure the internal forces. The bridge deflection was measured at

mid-span underneath the longitudinal bottom chord using a displacement transducer. In the

beginning of the test, a dial gauge was set aside the displacement transducer, as shown in the

Figure 3, to verify whether the obtained deflection was reasonable.

Figure 3: Test Model and Experimental Setup.

During the verification stage, the mini radio-controlled kid-car was pulled forward with a

very low speed (0.011 m/s) to allow the vertical deflection of the truss could be detected by

the dial gage. Results from the first series revealed the unexpected rebound behavior of the

vertical deflection of the Wr1 truss model (details are shown in the subsequence section). The

vertical deflection behavior was then become the point of interested in this study.

The direction of the second series of the experiment had been changed aimed to validate

the behavior of the same types of Pratt and Warren trusses with the different dimension. The

specimens were then designed as the Pt2 and Wr2 by reducing only the height of the truss

bridge. Results obtained from the second series of the Wr2 truss model also indicated the

rebound behavior of the vertical deflection at the mid span point.


291



3. Analytical Models Complementary to the experimental investigation, analytical models were conducted on

the laboratory scaled truss bridge behavior. Two methodologies of the analytical models were

selected. This included the traditional method of virtual work and numerical method using

the available commercial finite element software.

3.1 Traditional Analysis (Method of Virtual Work) By applying the virtual work for the coplanar truss system, the weight of the car were

considered as a row of two concentrated live loads and applied at the bottom chord of the

truss. The row of loads was referred as the Car loads F1 and F2 as shown in the Figure 4.

Figure 4: Car Load Distribution for 2-D Analysis.

To determine the internal forces developed in each member, the two important

assumptions for analysis a truss needs to be included (Hibbeller., R. C., and Yap., K. B.,

2012). The first assumption states that the truss members are joined together by smooth pins.

The second one requires that all loading are applied at the joint. This assumption could be

satisfied by allowing the front wheel to be placed at any joint of the truss. The Car loads F1

could be directly transformed to the Equivalent car load P1 as shown in the Figure 4.

However, the Car loads F2 might need to apply the linear interpolation function to transform

into the Equivalent car load P2 and P3.

Once the internal forces are obtained, many method of structural analysis can be

performed to find the vertical deflection at the mid span of the truss bridge analytical models.

In the case of the virtual work method (Laible, J. P., 1985), the displacement of a truss joint

can be determined from direct application of the following equation.

1 ∙ ∆ = ∑p∙P𝐴𝐸

L (1),

F1 F2

P2 P1 P3

78 cm x

v

Car load

Equivalent car load

F1 F2

P1 P3

78 cm x

v

Car load

Equivalent car load

P2

(a) Pt1 and Pt2 Models (b) Wr1 and Wr2 Models


Where ∆ = external joint displacement, p = internal virtual normal force caused by the

external virtual unit load, P = internal normal force member caused by the real load, L =

length of a member, A= cross-sectional area of a member, and E = modulus of elasticity of a

member.

Results obtained from the method of virtual work of the four models (e.g., Pt1, Wr1,

Pt2 and Wr2) provide the similar manner. The rebound behaviour of the Wr1 and Wr2

models could not be detected by the traditional analysis.

Figure 5: Comparison of vertical deflection history at mid-span of Pt1 and Wr1

3.2 Numerical Analysis (Finite Element Method) Finite element method, the static analysis of the simple 2-D truss analysis, was

performed aiming to verify whether the unexpected rebound of the Wr1and Wr2 models could

be detected. A commercial software was selected for this purpose. Since the geometry is

very simple (only truss members and joints), nodes and elements (two-dimensional truss

element) were directly created by the software. The areas of the top and bottom chords were *Corresponding author (C.Pisitpaibool). Tel/Fax: +66-2-5643001 Ext.3102. E-mail address: [email protected]. 2014. International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies. Volume 5 No.4 ISSN 2228-9860 eISSN 1906-9642. Online available at http://tuengr.com/V05/0287.pdf.

293



0.89 cm2, while the areas of the diagonal and vertical members were 0.283 cm2. E = 2.04x106

ksc. The parameter of interested and presented in this paper is only the vertical deflection at

the mid-span point. The car load distribution applied in this case followed the one presented

in the Figure 3.

Figure 6: Comparison of vertical deflection history at mid-span of Pt2 and Wr2.

4. Results Figure5 shows the comparison of the typical mid-span deflection obtained from the First

series, Pt1 and Wr1. Most lines behave in such a normal manner, except the blue lines of the

Wr1, which represents results from the laboratory. The blue lines of Wr1 appears that the

mid-span deflection slightly rebound when the front wheel is approximately located at the

distances ranged from 1.25 m to 2.25.

Figure 6 shows the comparison of the typical mid-span deflection obtained from the

Second series, Pt2 andWr2. Most lines behave in such a normal manner equivalent to the

results from the First series. The blue lines of the of Wr2, which represents results from the

laboratory model, also appears that the mid-span deflection slightly rebound when the front


wheel is approximately located at the distances ranged from 1.25 m to 2.25

Although the rebound behavior of the Warren type truss bridge (Wr1 andWr2) is in a

small magnitude, this response is unexpected to be found and cannot be detected by the elastic

static analysis, such as the virtual work and finite element. Static analysis is chosen since the

car is moved by pulling forward with a very low speed (0.50 m per 45 second or 0.011 m/s)

5. Discussion The investigation indicated that the rebound of the vertical deflection obtained from the

experiment of the Warren truss models could not be taken into account by the traditional and

numerical analysis procedures.

Several sources addressing below may be the source causing this behavior.

1. The geometric arrangement of the diagonal members especially the two bars which form the

liked A-shape at the mid-span of the bridge.

2. The spacing of the bracing under the Warren is quite large comparing with those of the Pratt

truss. Some amount of applied load may be directly transferred to the joints that far from the

mid span but close to the both ends.

3. The combination between the truss loads and the truss weight used in this investigation.

It should be noted that when the position of front wheel is approximately 1 m, the rear

wheel just be located on the desk. In addition, when the distance is of approximately 2.75 m,

the front wheel just get off from the bridge desk. This means the rebound deflection occurs

when all wheels are on the bridge. Since the bridge span (2.50 m) is not significant greater

than the span length (0.78 m) of the car wheels, when the car is at the mid-point the distance

from each wheels to the nearer supports are very small (0.86 m-by symmetry). With the

combination of the geometric arrangement of the members in the A-shape at mid span, most

of loads may be directly distributed to both sides of the supports instead of the mid-span.

This reduces the load at the mid span resulting to the lesser deflection and consequently the

rebound of the behavior.

In order to find the exactly parameters affecting this behavior, future study is required.

Moreover, other similar models, such as the Warren truss with the V-shape at mid-span, may

need to be constructed and performed the comparison of their response.


295



6. Conclusion Two series of the laboratory-scaled parallel chorded truss bridges under the moving car

loads were conducted. Each series of the experiments included two traditional types of the

steel bridge trusses, which were in the form of the Pratt and Warren types. A mini radio-

controlled kid-car was used as the loads applied on the bottom parallel chords of the models

with a low speed. The experimental programs addressed the unexpected rebound behavior of

the vertical deflection of the Warren truss models under the low speed of the moving car

loads. This behavior, however, cannot be detected by the traditional and numerical analysis

methods. Further study is required to clarify the parameter influencing the rebound behavior

of the Warren truss model.

7. Acknowledgements The authors gratefully acknowledge the contributions of Mr. Worapoj and Mr.

Prothompong for their help in providing some instrumentation for this study.

8. References Bacinskas, D., Kamatis, Z., Jatulis, D., and Kilikevicius, A., (2013), Field Testing of Old

Narrow-Gauge Railway Steel Truss Bridge,Procedia Engineering, 57 (2013) 136-43.

Brunell, G. and Kim, Y.J. (2013), Effect of Local Damage on the Behavior of a laboratory-scale steel truss bridge. Engineering Structures, 48(2013), 281-291.

Cheng, B., Qian, G., and Sun, H., (2013), Steel Truss Bridges with Welded Box-Section Members and Bowknot Integral Joints, Part I: Linear and Non-Linear Analysis, Journal of Constructional Steel Research, 80 (2013) 465-474.

Hibbeler, R. C., 2012, Mechanics for Engineers – Statics, Prentice Hall, Pearson Education South Asia Pte Ltd, Singapore.

Laible, J. P., 1985, Structural Analysis, CBS College Publishing, New York.

Surachet Charnrit is a student of Department of Civil Engineering, Faculty of Engineering at Thammasat University. His interests are in the areas of construction technology and management.

Weerayut Krahothong is a student of Department of Civil Engineering, Faculty of Engineering at Thammasat University. He is interested in applications of technology in construction and management.

Dr. Chaisak Pisitpaibool is an Assistant Professor of Department of Civil Engineering at Thammasat University. He received his B.Eng. and M.Eng. from Khon Khaen University in 1991. He had gained the experience as a lecturer in Chiang Mai University before moving to the Thammasat University. He then continued his PhD study at Nottingham University, UK, where he obtained his PhD in 2003. His research interest encompasses laboratory modeling of structures.




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