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
Citation
SONG, Ruidian; LAU, Hoong Chuin; LUO, Xue; and ZHAO, Lei.
Coordinated delivery to shopping malls with limited docking capacity. (2022). Transportation Science. 56, (2), 501-527.
Available at: https://ink.library.smu.edu.sg/sis_research/6233
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Supplementary file
Additional URL
https://doi.org/10.1287/trsc.2021.1109
Included in
Numerical Analysis and Scientific Computing Commons, Operations and Supply Chain Management Commons, Operations Research, Systems Engineering and Industrial Engineering Commons