An optimization method for bike-sharing deployment based on the first-and-last mile accessibility improvement

Cycling mobility is higher than walking mobility, making it a viable solution for the first-and-last mile issues to improve public transport accessibility. With the promotion of bike-sharing, it can be used as an alternative mode of transportation for the first-and-last mile, improving the impact on public transport accessibility. This study proposes an optimization method for deploying bike-sharing systems to enhance first-and-last mile accessibility, aiming to quantify the resulting accessibility gains and identify the optimal bike allocation. Using a full transportation trip chain model, the study compares accessibility changes within transit station buffer zones before and after integrating bike-sharing for first-and-last mile travel. Then an optimization model suitable for the situation in Beijing, China is established, which considers the improvement of accessibility through introducing the bike-sharing in the first-and-last mile, using an adaptive genetic algorithm to adjust the deployment of bike-sharing. Additionally, the model includes a two-dimensional bike-sharing deployment optimization framework, which addresses both the meso-level model allocated to stations and the micro-level model allocated to AOIs. This model comprehensively considers the population distribution around stations, the number of jobs, and the accessibility differences brought by various calculation methods. It aims to improve the overall efficiency of the public transportation system while promoting the development of green urban transportation. Empirical research indicates that the introduction and rational layout of bike-sharing system significantly enhances the efficiency of the first-and-last mile, providing robust decision support for urban transportation planning and bike-sharing operations.