A Maximum Capture Problem for Public Bicycle Station Allocation and Bicycle Network Design

Bike-sharing systems (BSS) constitute a fundamental component of sustainable transportation development, significantly reducing the dependence on private vehicles, mitigating traffic congestion, and addressing environmental challenges in densely populated urban areas. This study develops a maximum capture problem designed to optimize bike lane network design, with the dual objective of maximizing user adoption and spatial equity by addressing disparities in service accessibility across diverse BSS station locations. The proposed problem employs the Multinomial Logit (MNL) travel choice behavior. The independence of irrelevant alternatives (IIA) property of used to provides a mixed-integer linear programming (MILP) formulation. Through numerical examples of the Chaing Mai transportation network, the proposed MILP can determine the bike lane network and BSS station location to optimize the number of users. Multimodal transport is a key factor in promoting BSS usage, where both the BSS and public transit gain win-win situations. Spatial equity and transportation network characteristics play significant roles in determining the optimum BSS station location. A unit change in the MNL dispersion parameter has a high impact on the bike modal shift, the spatial equity, and bike usage distance travelled.