Publication Type

Journal Article

Version

submittedVersion

Publication Date

3-2022

Abstract

Shopping malls are densely located in major cities such as Singapore and Hong Kong. Tenants in these shopping malls generate a large number of freight orders to their contracted logistics service providers, who independently plan their own delivery schedules. These uncoordinated deliveries and limited docking capacity jointly cause congestion at the shopping malls. A delivery coordination platform centrally plans the vehicle routes for the logistics service providers and simultaneously schedules the dock time slots at the shopping malls for the delivery orders. Vehicle routing and dock scheduling decisions need to be made jointly against the backdrop of travel time and service time uncertainty and subject to practical operations rules. We model this problem as a two-stage stochastic mixed integer program, develop an Adaptive Large Neighborhood Search algorithm that approximates the second stage recourse function using various sample sizes, and examine the associated in-sample and out-of-sample stability. Our numerical study on a testbed of instances based on real data in Singapore demonstrates the value of coordination and the value of stochastic solutions.

Keywords

Coordinated delivery, Docking capacity, Endogenous time window, Stochastic travel and service times, Adaptive large neighborhood search

Discipline

Numerical Analysis and Scientific Computing | Operations and Supply Chain Management | Operations Research, Systems Engineering and Industrial Engineering

Research Areas

Intelligent Systems and Optimization

Publication

Transportation Science

Volume

56

Issue

2

First Page

501

Last Page

527

ISSN

0041-1655

Identifier

10.1287/trsc.2021.1109

Publisher

INFORMS

Embargo Period

11-2-2021

Copyright Owner and License

Authors

TSci 2021 mall-delivery-appendices.pdf (477 kB)
Supplementary file

Additional URL

https://doi.org/10.1287/trsc.2021.1109

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