Plan Your System and Price for Free: Fast Algorithms for Multimodal Transit Operations

Siddhartha Banerjee (), Chamsi Hssaine (), Qi Luo () and Samitha Samaranayake ()
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Siddhartha Banerjee: Department of Operations Research and Information Engineering, Cornell University, Ithaca, New York 14853
Chamsi Hssaine: Department of Data Sciences and Operations, Marshall School of Business, University of Southern California, Los Angeles, California 90089
Qi Luo: Department of Business Analytics, Tippie College of Business, University of Iowa, Iowa City, Iowa 52242
Samitha Samaranayake: School of Civil and Environmental Engineering, Cornell University, Ithaca, New York 14853

Transportation Science, 2025, vol. 59, issue 1, 13-27

Abstract: We study the problem of jointly pricing and designing a smart transit system, where a transit agency (the platform ) controls a fleet of demand-responsive vehicles (cars) and a fixed line service (buses). The platform offers commuters a menu of options ( modes ) to travel between origin and destination (e.g., direct car trip, a bus ride, or a combination of the two), and commuters make a utility-maximizing choice within this menu, given the price of each mode. The goal of the platform is to determine an optimal set of modes to display to commuters, prices for these modes, and the design of the transit network in order to maximize the social welfare of the system. In this work, we tackle the commuter choice aspect of this problem, traditionally approached via computationally intensive bilevel programming techniques. In particular, we develop a framework that efficiently decouples the pricing and network design problem: Given an efficient (approximation) algorithm for centralized network design without prices , there exists an efficient (approximation) algorithm for decentralized network design with prices and commuter choice . We demonstrate the practicality of our framework via extensive numerical experiments on a real-world data set. We moreover explore the dependence of metrics such as welfare, revenue, and mode usage on (i) transfer costs and (ii) cost of contracting with on-demand service providers and exhibit the welfare gains of a fully integrated mobility system.

Keywords: multimodal transportation; pricing; network design (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:inm:ortrsc:v:59:y:2025:i:1:p:13-27

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