Joint Optimization of Transfer Location and Capacity in a Multimodal Transport Network: Bilevel Modeling and Paradoxes

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. Numerical studies are conducted to demonstrate the existence and examine two Braess like paradox phenomena in a multimodal transport network. The first one states that under fixed demand constructing parking spaces to stimulate the usage of Park and Ride service could deteriorate the system performance, measured by the total passengers travel time, while the second one reveals that under variable demand increasing the parking capacity for the Park and Ride services to promote the usages may fail, represented by the decline in its modal share. Meanwhile, the last experiment suggests that constructing transfer infrastructures at distributed stations outperforms building a large transfer center in terms of attracting travelers using sustainable transit modes.