Joint Optimization of Transfer Location and Capacity in a Multimodal Transport Network: Bilevel Modeling and Paradoxes
Yu Jiang, Jiao Ye, Jun Chen

TL;DR
This paper presents a bilevel model for optimizing transfer location and capacity in multimodal transport networks, revealing paradoxes where increasing infrastructure can worsen system performance and suggesting distributed stations are more effective.
Contribution
It develops a novel bilevel mixed integer linear programming model with a matheuristics solution approach for multimodal infrastructure planning.
Findings
Constructing parking to boost Park and Ride can worsen travel times.
Increasing parking capacity may reduce modal share of Park and Ride.
Distributed transfer stations outperform large centers for attracting travelers.
Abstract
With the growing attention towards developing the multimodal transport system to enhance urban mobility, there is an increasing need to construct new, rebuild or expand existing infrastructure to facilitate existing and accommodate newly generated travel demand. Therefore, this paper develops a bilevel model to simultaneously determine the location and capacity of the transfer infrastructure to be built considering elastic demand in a multimodal transport network. The upper level problem is formulated as a mixed integer linear programming problem, while the lower level problem is the capacitated combined trip distribution assignment model that depicts both destination and route choices of travelers via the multinomial logit formula. To solve the model, the paper develops a matheuristics algorithm that integrates a Genetic Algorithm and a successive linear programming solution approach.…
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Taxonomy
TopicsTransportation Planning and Optimization · Smart Parking Systems Research · Transportation and Mobility Innovations
