united parcel service naafn - ground senior design final presentation april 15, 2008 jessel...
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United Parcel Service United Parcel Service NAAFN - GroundNAAFN - Ground
Senior Design
Final Presentation
April 15, 2008
Jessel Dhabliwala, Megan Patrick, Tom Pelling, Nathan Petty, Vikas Venugopal, Selin Yilmaz
This presentation has been created in the framework of a student design project and it is neither officially sanctioned by the Georgia Institute of Technology nor the United Parcel Service.
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OutlineOutline• Client Description• Problem Description• Design Strategy
– Truckload Demand Generator– Independent Lane Scheduling Model
• Integrated Approach– Stochastic Optimization
• Results• Conclusion
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UPS North American Air Freight Network (NAAFN)
• Large Third Party Logistics (3PL)
• Product Offerings of NAAFN– Next Day– Second Day– Economy/Deferred Delivery
• Ground Truck Movements– Scheduled Movements – Ad-hoc Movements
Client DescriptionClient Description
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FLL
MSY
MOB
MIA Gateway
BHM
BTR
JAN
CID
MKE
GRB
MSN
TUS
SAN
LAS
YOWBGR
PVD
PSM
OKC
SAT
GRR
SJC
PHX
PWMBTV
BOS
ROA
BUF
SBN
YYZROC
MLI
SYR
ERITTN
TRI
MDTSLC
SEA
BOI
GEG
GSP
MEMLIT
ABE
JFK Gateway
IAH
COS
RNO
PDX
JFK
IAD
ORF
PHL
RIC
EWR
GSOTYS
ONT
SHV
LAX Gateway
PSC
FAT
CHA
RFD MDW
BWI
YUL
BGMELM
BDL
TLH
CHS
CAE
RDU
FAY ILM
WIL
LBB
AMA
MAF
TUL
FSM
JLN
FYV
TPA
OAKDEN
SAC
ALB
JAX
AVL
ATL
ORDGateway
HSVFLO
ELP
LRD
BRO
ACT
AUS
ATLGateway
ABQ
FNT
DTW
TOL CLE
IND
FWA
CMIPIA
STL
EVV
MCI
ICT
OMA
MSP
DSM
SDF
BNA
LEX
CVG
DAYCMH
PIT
PKB
CRW
SWF
CLT
MCO
DFW
LAX
Regional Hub Ground NetworkRegional Hub Ground Network
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Truckload Procurement ProcessTruckload Procurement Process
Determine Scheduled Moves per Lane
Build Routes to Cover Scheduled Moves
Obtain Carrier Bids for Routes
Award Route Contracts to Winning Bidders
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Project FocusProject Focus
Determine Scheduled Moves per Lane
Build Routes to Cover Scheduled Moves
Obtain Carrier Bids for Routes
Award Route Contracts to Winning Bidders
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UPS’s Current MethodUPS’s Current Method
Average Weekly Demand
Weekly Operating Days
Moves per Day
=
Determine Scheduled Moves per Lane
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Operational ProcessOperational Process
Scheduled Routes are Executed Weekly
Scenario Two
Demand > Scheduled
Dispatch ad-hoc truck(s)
Scenario One
Demand < Scheduled
Incur scheduled truck cost
OR
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DAILY VARIABILITY2007
100
120140
160180
200
MON TUE WED THUR FRI SAT
DAY OF WEEK
LBS
(MIL
LIO
NS)
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Design StrategyDesign Strategy
Integrated Model
Independent Lane
Scheduling Model
Truckload Demand
Generator
Detailed Cost Estimation
Model
Detailed Cost Estimation
Model
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Shipment Level OD
Demand Data
Chain Tables
Input
Includes:OD data, Day of departure,
Actual weight, GAD weight,
Miles
Functionality Output
Conversion
Trucks per lane per day
Convert to truckloads required on each lane each day
Assigns OD freight to
sequences of lanes
Truckload Demand GeneratorTruckload Demand Generator
Demand Histogram
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Design StrategyDesign Strategy
Truckload Demand
Generator
Integrated Model
Independent Lane
Scheduling Model
Detailed Cost Estimation
Model
Detailed Cost Estimation
Model
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Independent Lane
Scheduling Model
Input Functionality Output
Numberof moves toschedule on
each lane per day
Histograms from TDG
Lane Cost Estimates•Ad-hoc•Scheduled
Minimize expected costs per lane per day
Independent Lane Scheduling Independent Lane Scheduling ModelModel
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• Multiple Linear Regression
• R-squared = 0.752
n
iiiiiABAB COUTINdrY
1
)()()(
Ad-hoc Cost EstimationAd-hoc Cost Estimation
Where
• YAB = Ad-hoc cost from city A to city B
• β, α, d, C = Factor coefficients
• rAB = Distance in miles from city A to city B
• INi, OUTi = Indicates a move into or out of state i
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• Treats each lane individually
• Decides amount of moves to schedule (TS)
• Distributions (Ta) approximated by TDG
• Lane Cost = CS*TS+ E[CAH*MAX(0,TA-TS)]
Where:• CS = Cost of scheduled move on lane• CAH = Cost of an ad-hoc move on lane• TS = Amount of scheduled trucks• TA= Amount of actual trucks needed
ILSM FunctionalityILSM Functionality
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Detailed Cost EstimationDetailed Cost Estimation• Total Cost: Scheduled cost + Ad-hoc cost
• Two-Phase Approach– Phase I: Deterministic integer program
• Covers complete lane moves with pre-existing routes• Minimizes scheduled truck dispatch costs
– Phase II: Compute ad-hoc cost• Uses route schedule from phase I• Computes necessary ad-hoc moves and cost per day
from historical data
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ILSM ResultsILSM Results
• Possible Causes of Higher Cost:– Unbalanced routes
Scheduled Ad-hoc Total
UPS 2007 $70,900,000 $4,900,000 $75,800,000
ILSM $63,900,000 $18,300,000 $82,200,000
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Design StrategyDesign Strategy
Integrated Model
Independent Lane
Scheduling Model
Truckload Demand
Generator
Detailed Cost Estimation
Model
Detailed Cost Estimation
Model
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Integrated ModelIntegrated Model
• Integrates Scheduling and Costing– Stochastic programming model– Uses pre-existing NAAFN routes and costs– Selects routes to execute weekly
• Sample Average Approach– Generates n random weeks from TDG– Covers all moves in each scenario
• With a route or an ad-hoc move
• Minimize Sample Average Cost per Week
Xpress ModelXpress Model• Inputs
– Pre-existing routes, route costs, ad-hoc costs, and TDG frequency histograms
• Functionality– Random variables represent CDF of histogram– Number of constraints = n * number of unique lane-day
combinations• n = 50
– Over 125,000 constraints– Run time of three minutes
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Integrated Model ResultsIntegrated Model Results
• Results:
Concerns:– Extremely risky to depend on unscheduled moves– Sensitivity of model to ad-hoc cost estimates
Scheduled Ad-hoc Total
UPS 2007 $70,900,000 $4,900,000 $75,800,000
SA n=10 $33,000,000 $39,200,000 $72,200,000
SA n=50 $32,300,000 $37,100,000 $69,400,000
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ImprovementsImprovements• “Scheduling” Ad-hoc Movements
– One-way moves • Occur consistently throughout the year• Scheduled at ad-hoc price
Scheduled w/ Routes
Scheduled One-Way
Total Scheduled
Ad-hoc Total
UPS 2007 $70,900,000 --- $70,900,000 $4,900,000 $75,800,000
ILSM $63,900,000 $6,500,000 $70,400,000 $18,300,000 $88,700,000
SA n=50 $32,600,000 $21,000,000 $53,600,000 $15,800,000 $69,400,000
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ConclusionsConclusions
• Suggested Method– Integrated model
• Further Improvements– Scheduling one-ways
• Significant Potential for Cost Savings– Scheduling daily may save $6M annually
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RecommendationsRecommendations• Implementation
–Estimate daily demand per lane from TDG
–Generate new “candidate” routes
–Estimate new route costs
• Solve Integrated Model to select routes for bids
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QuestionsQuestions