Massachusetts Institute of Technology
A computational study of flexible routing strategies for the VRP with stochastic demands
Abstract
dc:description.abstractWe develop and numerically test a new strategy for the vehicle routing problem with stochastic customer demands. In our proposed approach, drivers are assigned to predetermined delivery routes in which adjacent routes share some customers. This overlapping assignment structure, which is inspired by the open chain design from the field of manufacturing process flexibility, enables drivers to adapt to variable customer demands while still maintaining largely consistent routes. Through an extensive computational study and scenario analysis, we show that relative to a system without customer sharing, such flexible routing strategies partly mitigate the transportation costs of filling unexpected customer demands, and the relative savings grow with the number of customers in the network. We also find that much of the cost savings is gained with just the first customer that is shared between adjacent routes. Thus, the overlapped routing model forms the basis for a practical and efficient strategy to manage costs from demand uncertainty.
Degree
thesis:*- Name thesis:degree_name
- Master
- Department dc:contributor.department
- Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
- Grantor dc:publisher
- Massachusetts Institute of Technology
- Year dc:date.issued
- 2021
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Ledvina, Kirby.
- Advisor dc:contributor.advisor
-
- David Simchi-Levi.
Subjects
dc:subject × 1Rights
dc:rights- Statement dc:rights
-
- MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.
- Licence dc:rights.uri
- Language dc:language.iso
- eng
Identifiers
dc:identifier.*- Handle dc:identifier.uri
- https://hdl.handle.net/1721.1/130822
- OAI identifier oai:identifier
- oai:dspace.mit.edu:1721.1/130822