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United Parcel Service NAAFN - Ground. Senior Design Final Presentation April 15, 2008 Jessel Dhabliwala, Megan Patrick, Tom Pelling, Nathan Petty, Vikas Venugopal, Selin Yilmaz.

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United parcel service naafn ground

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

Outline

Client Description

Problem Description

Design Strategy

Truckload Demand Generator

Independent Lane Scheduling Model

Integrated Approach

Stochastic Optimization

Results

Conclusion


United parcel service naafn ground

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 Description


United parcel service naafn ground

Regional Hub Ground Network

SEA

GEG

PSC

BGR

PDX

YUL

YOW

PWM

BTV

BOI

ALB

PSM

YYZ

MSP

GRB

ROC

SYR

BOS

BDL

PVD

FNT

BUF

MKE

MSN

SWF

ELM

GRR

BGM

DTW

JFK

CID

ABE

ERI

EWR

RFD

MDW

TOL

CLE

RNO

TTN

OMA

DSM

FWA

MDT

SLC

JFK

Gateway

PHL

SAC

ORD

Gateway

SBN

PIT

MLI

OAK

BWI

PIA

CMH

DEN

CMI

IND

DAY

PKB

IAD

SJC

MCI

CVG

FAT

RIC

STL

CRW

COS

LEX

ORF

ICT

EVV

SDF

ROA

LAS

TRI

GSO

JLN

WIL

LAX Gateway

RDU

TYS

TUL

LAX

ONT

BNA

FYV

AVL

MEM

CLT

FAY

ILM

OKC

CHA

LIT

FLO

ABQ

AMA

GSP

PHX

FSM

HSV

CAE

ATL

SAN

LBB

CHS

ATL

Gateway

TUS

BHM

DFW

JAN

SHV

ELP

MAF

JAX

MOB

ACT

BTR

TLH

IAH

MSY

AUS

LRD

MCO

SAT

TPA

FLL

BRO

MIA Gateway


Truckload procurement process

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


Project focus

Project Focus

Determine Scheduled Moves per Lane

Build Routes to Cover Scheduled Moves

Obtain Carrier Bids for Routes

Award Route Contracts to Winning Bidders


Ups s current method

UPS’s Current Method

Determine Scheduled Moves per Lane

Average Weekly Demand

Weekly Operating Days

Moves

per Day

=


Operational process

Operational Process

Scheduled Routes are Executed Weekly

Scenario One

Scenario Two

Demand < Scheduled

Incur scheduled truck cost

OR

Demand > Scheduled

Dispatch ad-hoc truck(s)


United parcel service naafn ground

Design Strategy

Independent Lane Scheduling Model

Detailed Cost Estimation Model

Truckload Demand Generator

Detailed Cost Estimation Model

Integrated Model


United parcel service naafn ground

Truckload Demand Generator

Input

Functionality

Output

Shipment

Level OD

Demand Data

Chain Tables

Demand Histogram

Conversion

Includes:

OD data, Day of departure, Actual weight, GAD weight, Miles

Assigns OD freight to sequences of lanes

Convert to truckloads required on each lane each day

Trucks per lane per day


United parcel service naafn ground

Design Strategy

Independent Lane Scheduling Model

Detailed Cost Estimation Model

Truckload Demand Generator

Detailed Cost Estimation Model

Integrated Model


United parcel service naafn ground

Independent Lane Scheduling Model

Input

Functionality

Output

Histograms from TDG

Lane Cost Estimates

  • Ad-hoc

  • Scheduled

Independent Lane Scheduling

Model

Number

of moves to

schedule on

each lane

per day

Minimize expected costs per lane per day


United parcel service naafn ground

Multiple Linear Regression

R-squared = 0.752

Ad-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


United parcel service naafn ground

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


Detailed cost estimation

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


Ilsm results

ILSM Results

Possible Causes of Higher Cost:

Unbalanced routes


United parcel service naafn ground

Design Strategy

Independent Lane Scheduling Model

Detailed Cost Estimation Model

Truckload Demand Generator

Detailed Cost Estimation Model

Integrated Model


Integrated model

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


United parcel service naafn ground

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

Integrated Model Results

  • Results:

  • Concerns:

    • Extremely risky to depend on unscheduled moves

    • Sensitivity of model to ad-hoc cost estimates


Improvements

Improvements

  • “Scheduling” Ad-hoc Movements

    • One-way moves

      • Occur consistently throughout the year

      • Scheduled at ad-hoc price


Conclusions

Conclusions

  • Suggested Method

    • Integrated model

  • Further Improvements

    • Scheduling one-ways

  • Significant Potential for Cost Savings

    • Scheduling daily may save $6M annually


Recommendations

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


Questions

Questions


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