United Parcel Service
NAAFN - 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.
Outline
• Client Description
• Problem Description
• Design Strategy
– Truckload Demand Generator
– Independent Lane Scheduling Model
• Integrated Approach
– Stochastic Optimization
• Results
• Conclusion
2
Client Description
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
3
Regional Hub Ground Network
SEA
PSC
GEG
PDX
BOI
MSP
YYZ
GRB
MSN MKE
CID
RNO
OMA
SLC
SAC
OAK
SJC
FAT
LAX Gateway
ICT
LAS
CVG
STL
EVV SDF
JLN
FYV
ABQ
PHX
SAN
AMA
OKC
FSM
MEM
BNA
HSV
LBB
TUS
BHM
DFW
ELP
ACT
AUS
LRD
JAN
SHV
MAF
SAT
MOB
BTR
IAH
AVL
CHA
LIT
MSY
TRI
PWM
PSM
BOS
BDL
PVD
SWF
BGM
ABE EWR JFK
TTN
MDT
PHL JFK
Gateway
BWI
IAD
RIC
CRW
LEX
TYS
TUL
ONT
BTV
BUF
ELM
ERI
TOL CLE
FWA
ORD SBN
PIT
MLI
PIAGateway
CMH
CMI IND DAY
PKB
MCI
COS
FNT
GRR DTW
BGR
ALB
ROC SYR
RFD MDW
DSM
DEN
LAX
YUL
YOW
ORF
RO
A GSO
WIL
RDU
CLT
FAY
FLO
CAE
GSP
ATL
ILM
CHS
ATL
Gateway
JAX
TLH
MCO
TPA
FLL
BRO
MIA Gateway
4
Truckload Procurement Process
Determine Scheduled Moves per Lane
Build Routes to Cover Scheduled Moves
Obtain Carrier Bids for Routes
Award Route Contracts to
Winning Bidders
5
Project Focus
Determine Scheduled Moves per Lane
Build Routes to Cover Scheduled Moves
Obtain Carrier Bids for Routes
Award Route Contracts to
Winning Bidders
6
UPS’s Current Method
Determine Scheduled Moves per Lane
Average Weekly Demand
Weekly Operating Days
=
Moves
per Day
7
Operational Process
Scheduled Routes are Executed Weekly
Scenario One
Demand < Scheduled
Incur scheduled truck cost
Scenario Two
OR
Demand > Scheduled
Dispatch ad-hoc truck(s)
8
DAILY VARIABILITY
LBS (MILLIONS)
2007
200
180
160
140
120
100
MON
TUE
WED
THUR
FRI
SAT
DAY OF WEEK
9
Design Strategy
Independent
Lane
Scheduling
Model
Detailed Cost
Estimation
Model
Truckload
Demand
Generator
Integrated
Model
Detailed Cost
Estimation
Model
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Truckload Demand Generator
Input
Functionality
Shipment
Level OD
Demand Data
Chain
Tables
Includes:
OD data, Day
of departure,
Actual weight,
GAD weight,
Miles
Assigns OD
freight to
sequences of
lanes
Conversion
Convert to
truckloads
required on
each lane
each day
Output
Demand
Histogram
Trucks
per lane
per day
11
12
Design Strategy
Independent
Lane
Scheduling
Model
Detailed Cost
Estimation
Model
Truckload
Demand
Generator
Integrated
Model
Detailed Cost
Estimation
Model
13
Independent Lane Scheduling
Model
Input
Histograms from
TDG
Lane Cost Estimates
•Ad-hoc
•Scheduled
Functionality
Independent
Lane
Scheduling
Model
Output
Number
of moves to
schedule on
each lane
per day
Minimize expected costs per lane
per day
14
Ad-hoc Cost Estimation
• Multiple Linear Regression
• R-squared = 0.752
n
YAB  (rAB )d   ( IN i ) i  (OUTi )  i   C
i 1
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
15
ILSM Functionality
• 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
16
Detailed 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
17
ILSM Results
Scheduled
UPS 2007
ILSM
$70,900,000
Ad-hoc
Total
$4,900,000 $75,800,000
$63,900,000 $18,300,000 $82,200,000
• Possible Causes of Higher Cost:
– Unbalanced routes
18
Design Strategy
Independent
Lane
Scheduling
Model
Detailed Cost
Estimation
Model
Truckload
Demand
Generator
Integrated
Model
Detailed Cost
Estimation
Model
19
Integrated 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
20
Xpress 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
Integrated Model Results
• Results:
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
Concerns:
– Extremely risky to depend on unscheduled moves
– Sensitivity of model to ad-hoc cost estimates
22
Improvements
• “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
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
Ad-hoc
Total
23
Conclusions
• Suggested Method
– Integrated model
• Further Improvements
– Scheduling one-ways
• Significant Potential for Cost Savings
– Scheduling daily may save $6M annually
24
Recommendations
• Implementation
–Estimate daily demand per lane from TDG
–Generate new “candidate” routes
–Estimate new route costs
• Solve Integrated Model to select routes for bids
25
Questions
26