Battery swapping station location routing problem: A Cooperative Business Model

In the context of green logistics, the promotion of electric logistics vehicles is gaining momentum, but the process is constrained by insufficient infrastructure, such as battery swapping stations (BSSs). The high costs of BSS make it challenging for companies to expand their construction, while the low penetration rate of EVs further diminishes the investment value and motivation, creating a circular dependency problem. To address this challenge, cooperative models can be employed to lower investment barriers through cost sharing and encourage broader enterprise participation in constructing BSSs. This study focuses on the battery swapping station location-routing problem (BSS-LRP) by introducing a ”Cooperative Business Model” in which logistics companies can complete or participate in BSSs construction based on their operational needs. The model considers battery electric vehicles (BEVs) load, range, etc., and aims to minimize the investment, usage, and BEVs transport costs of BSSs. A heuristic algorithm, Simulated Annealing-K-Means-Ant Colony Optimization (SA-K-Means-ACO), is designed to solve this problem. The effectiveness and accuracy of the proposed algorithm have been validated by comparing it with the TS-ACO algorithm, especially when dealing with clustered customer instances. Furthermore, research conducted a comprehensive experiment to discuss the impact of battery capacity, Investment, and usage costs, offering insights for logistics companies.