Bilevel optimization for on-demand multimodal transit systems

Başçiftçi, Beste and Van Hentenryck, Pascal (2020) Bilevel optimization for on-demand multimodal transit systems. In: 17th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, CPAIOR 2020, Vienna, Austria

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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: Papers in Conference Proceedings
Uncontrolled Keywords: Benders decomposition; Bilevel optimization; Combinatorial cuts; Mode choice; On-demand transit system
Divisions: Faculty of Engineering and Natural Sciences
Depositing User: Beste Başçiftçi
Date Deposited: 04 Aug 2023 14:00
Last Modified: 04 Aug 2023 14:00

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