NETWORK ANALYSISFOR

SHORTEST OPTIMUM PATH

- SOURABH JAIN

What is network analysis ?

It enables you to solve problems such as :• Finding most efficient travel route • generating travel directions• finding closest facility• Defining service areas

OPTIMUM ROUTEThe selection of the optimum route may bedifferent according to our purpose and hencemay depend upon various factors such as :

• Most cost efficient routebased on :Time impedanceDistance impedance

• Most scenic route

CASE STUDIES

A COMPARITIVE ANALYSIS…

Study area

(Population)

New Delhi(national capital)

11 million

Tehran(capital of Iran)

8.5 million

Year of study 2013 2008

Objective Optimum path for tourism

Finding optimum path in dynamic

network

Impedances used

TimeOr

distance

Timeand

distance

Data used • IRS P6 satellite data

(sensor: LISS-IV)• SOI toposheet’s• ROW maps (by

DDA)

• SINA 1 satellite data

(sensor: PAN)

•Data from CCTV camera

Methodology Static analysis+

Time dependent dynamic analysis

of predictive nature

Static analysis+

Time dependent dynamic analysis of instantaneous and un-predictive

nature

• STEP 1 : Digitization of satellite data

DELHI• STEP 2 : Attaching attributes to roads

• STEP 3 : Use network analyst tool to find : quickest routeShortest route

• STEP 1 : Digitization.• STEP 2 : Attaching attributes.• STEP 3 : Use of network analyst tool to find

the shortest route using distance as impedance.

TEHRAN

• STEP 4 : Local Optimization and Partitioning

• STEP 5 : Using heuristic method to find the quickest route.

RESULTS OF THE COMPARITIVE STUDY

• Travel time of a journey is a function of traffic situation and can never have a predictive nature (as considered in Delhi case study).

• The dynamic analysis with time having a predictive nature will always give results including approximation.

THE SHORTEST ROUTE TO HAPPINESS

AIM : to suggest user a short and pleasant pathbetween their current location and destination .

SOURCES OF DATA

• Crowd sourcing• Flickr , foursquare metadata• Google street view• GPS• Virtual geographic system• geographical map

METHODOLOGY• STEP 1 :Vectorization of the maps available and markingall the location of the city under study.

• STEP 2 :Crowdsourcing people’s perceptions of theselocations along three dimensions:

beautyQuiethappy

• STEP 3 :An origin (O) and a destination (D) are selectedand M shortest paths between them are foundusing EPPSTEIN’S ALGORITHM.

EPPSTEIN’S ALGORITHM

• STEP 4 :Assign score to the paths along each of threeparameters, i.e. beauty, quiet and happy.

Shortest Beauty Happy Quiet

a b d c

b c b d

c a a c

d d c a

• STEP 5 :Select best path between origin and destinationwith right balance between short and pleasant.

RESULTS

• On an average the suggested paths are only 12% longer .

• Beautiful paths are on an average 28% more beautiful then shortest paths.

REFERENCES• Research paper “The shortest path to happiness : Recommending

Beautiful, Quiet and Happy routes in the city” by Yahoo labs [Barcelona, (Spain)] and University of Torino (Italy).

• http://www.isi.edu/natural-language/people/epp-cs562.pdf (for eppstein’s algorithm).

• IDOSI published “New Method for Finding Optimal Path in Dynamic Networks” (world applied sciences journal 3 (supple 1) 2008)

• “identification of optimum path for tourist places using GIS based network analysis” (IJARSGG (2013) Vol. 1, No. 2, 34-38)

THANK YOU