The Robust Vehicle Routing Problem with Time Window Assignments
Name
RVRP_TWA_TechReport.pdf
Description
Submitted version
Size
702.39 KB
Format
Adobe PDF
Checksum (MD5)
479cedc1e3200f3d959d4f7b6807189d
Author(s)
Hoogeboom, Maaike
Adulyasak, Yossiri
Dullaert, Wout
Jaillet, Patrick
Date Issued
2021
Journal
Transportation Science
Publisher
Institute for Operations Research and the Management Sciences (INFORMS)
Citation
Hoogeboom, Maaike, Adulyasak, Yossiri, Dullaert, Wout and Jaillet, Patrick. 2021. "The Robust Vehicle Routing Problem with Time Window Assignments." Transportation Science, 55 (2).
Version
Original manuscript
Abstract
In practice, there are several applications in which logistics service providers determine the service time windows at the customers, for example, in parcel delivery, retail, and repair services. These companies face uncertain travel times and service times that have to be taken into account when determining the time windows and routes prior to departure. The objective of the proposed robust vehicle routing problem with time window assignments (RVRP-TWA) is to simultaneously determine routes and time window assignments such that the expected travel time and the risk of violating the time windows are minimized. We assume that the travel time probability distributions are not completely known but that some statistics, such as the mean, minimum, and maximum, can be estimated. We extend the robust framework based on the requirements’ violation index, which was originally developed for the case where the specific requirements (time windows) are given as inputs, to the case where they are also part of the decisions. The subproblem of finding the optimal time window assignment for the customers in a given route is shown to be convex, and the subgradients can be derived. The RVRP-TWA is solved by iteratively generating subgradient cuts from the subproblem that are added in a branch-and-cut fashion. Experiments address the performance of the proposed solution approach and examine the trade-off between expected travel time and risk of violating the time windows.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Operations Research Center
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1287/TRSC.2020.1013
