Choice-driven dial-a-ride problem for demand responsive mobility service

Journal Article (2022)
Authors

S. Azadeh (École Polytechnique Fédérale de Lausanne, Transport and Planning, Massachusetts Institute of Technology)

B. Atasoy (TU Delft - Transport Engineering and Logistics, Massachusetts Institute of Technology)

Moshe E. Ben-Akiva (Massachusetts Institute of Technology)

Michel Bierlaire (École Polytechnique Fédérale de Lausanne)

Yousef Maknoon (École Polytechnique Fédérale de Lausanne, TU Delft - Transport and Logistics, Massachusetts Institute of Technology)

Research Group
Transport Engineering and Logistics
Copyright
© 2022 S. Sharif Azadeh, B. Atasoy, Moshe E. Ben-Akiva, M. Bierlaire, M.Y. Maknoon
To reference this document use:
https://doi.org/10.1016/j.trb.2022.04.008
More Info
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Publication Year
2022
Language
English
Copyright
© 2022 S. Sharif Azadeh, B. Atasoy, Moshe E. Ben-Akiva, M. Bierlaire, M.Y. Maknoon
Research Group
Transport Engineering and Logistics
Volume number
161
Pages (from-to)
128-149
DOI:
https://doi.org/10.1016/j.trb.2022.04.008
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Abstract

Urban mobility services face the challenge of planning their operations efficiently while complying with user preferences. In this paper, we introduce a new mathematical model called a choice-driven dial-a-ride problem (CD-DARP) which is a generalization of the dynamic DARP where passenger behavior is integrated in the operational planning using choice models and assortment optimization. We look at two types of mobility services, private and shared. Our problem extends the dynamic DARP by (i) changing its objective function to profit maximization, where both cost and revenue are variables, and (ii) incorporating assortment optimization with routing decisions in a dynamic setting. We propose a pricing scheme based on a choice model designed to offer service alternatives at the time a customer makes a request. We introduce a tailored algorithm to efficiently solve the dynamic CD-DARP. Computational results indicate that our proposed approach outperforms dynamic DARP in terms of reducing routing costs and improving the number of customers served.