Massachusetts Institute of Technology
Robust transportation network design under user equilibrium
Abstract
dc:description.abstractWe address the problem of designing a transportation network in the presence of demand uncertainty, multiple origin-destination pairs and a budget constraint for the overall construction cost, under the behavioral assumption that travelers optimize their own travel costs (i.e., the "user-equilibrium" condition). Under deterministic demand, we propose an exact integer optimization approach that leads to a quadratic objective, linear constraints optimization problem. As a result, the problem is efficiently solvable via commercial software, when the costs are linear functions of traffic flows. We then use an iterative algorithm to address the case of nonlinear cost functions. While the problem is intractable under probabilistic assumptions on demand uncertainty, we extend the previous model and propose an iterative algorithm using a robust optimization approach that models demand uncertainty. We finally report extensive numerical results to illustrate that our approach leads to tractable solutions for large scale networks.
Degree
thesis:*- Department dc:contributor.department
- Massachusetts Institute of Technology. Computation for Design and Optimization Program.
- Grantor dc:publisher
- Massachusetts Institute of Technology
- Year dc:date.issued
- 2007
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Lu, Yun
- Advisor dc:contributor.advisor
-
- Dimitris J. Bertsimas and Georgia Perakis.
Subjects
dc:subject × 1Rights
dc:rights- Statement dc:rights
-
- M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
- Licence dc:rights.uri
- Language dc:language.iso
- eng
Identifiers
dc:identifier.*- Handle dc:identifier.uri
- http://hdl.handle.net/1721.1/41731
- OAI identifier oai:identifier
- oai:dspace.mit.edu:1721.1/41731