An immune algorithm for solving the optimization problem of locating the battery swapping stations

Compared with fuel-powered vehicles, new energy electric vehicles have less carbon emissions. The application of new energy electric vehicles in logistics transportation is very significant to reduce vehicle-emitted greenhouse gases and improve environmental protection. In the logistics network using electric transport vehicles, the reasonable layout of battery swapping stations not only improves the distribution efficiency but also saves the distribution cost. In this paper, an integer programming problem model was formulated for reasonably locating battery swapping stations, where the total costs (including construction costs, operation and maintenance costs, and travel costs) were minimized. To solve this problem, we proposed a solution strategy based on an immune optimization algorithm, two crossover operators, and variable crossover and mutation rates. The effectiveness of the presented model and the performance of the proposed solution approach were evaluated using a case study. Compared with the commercial software CPLEX, the numerical results showed that the proposed algorithm can provide the optimal solution with less computing time.