Bilevel optimization for on-demand multimodal transit systems

Başçiftçi, Beste and Van Hentenryck, Pascal (2020) Bilevel optimization for on-demand multimodal transit systems. In: Hebrard, Emmanuel and Musliu, Nysret, (eds.) Integration of Constraint Programming, Artificial Intelligence, and Operations Research: 17th International Conference, CPAIOR 2020, Vienna, Austria, September 21–24, 2020, Proceedings. Lecture Notes in Computer Science, 12296. Springer International Publishing, Switzerland, pp. 52-68. ISBN 978-3-030-58941-7 (Print) 978-3-030-58942-4 (Online)

[thumbnail of CPAIOR Paper] PDF (CPAIOR Paper)
CPAIORPaper_AuthorVersion.pdf
Restricted to Repository staff only

Download (19MB) | Request a copy

Abstract

This study explores the design of an On-Demand Multimodal Transit System (ODMTS) that includes segmented mode switching models that decide whether potential riders adopt the new ODMTS or stay with their personal vehicles. It is motivated by the desire of transit agencies to design their network by taking into account both existing and latent demand, as quality of service improves. The paper presents a bilevel optimization where the leader problem designs the network and each rider has a follower problem to decide her best route through the ODMTS. The bilevel model is solved by a decomposition algorithm that combines traditional Benders cuts with combinatorial cuts to ensure the consistency of mode choices by the leader and follower problems. The approach is evaluated on a case study using historical data from Ann Arbor, Michigan, and a user choice model based on the income levels of the potential transit riders.
Item Type: Book Section / Chapter
Divisions: Faculty of Engineering and Natural Sciences > Academic programs > Industrial Engineering
Faculty of Engineering and Natural Sciences
Depositing User: Beste Başçiftçi
Date Deposited: 25 Sep 2020 18:17
Last Modified: 25 Sep 2020 18:17
URI: https://research.sabanciuniv.edu/id/eprint/40824

Actions (login required)

View Item
View Item