Electric Vehicle Charging Station Location-Routing Problem with Time Windows and Resource Sharing

Electric vehicles (EVs) are widely applied in logistics companies’ urban distribution, as fuel prices increase and environmental awareness grows. This study introduces an EV charging station (CS) location-routing problem with time windows resource sharing (EVCS-LRPTWRS). Resource sharing, among multiple depots within service periods is proposed to adjust the transportation configuration for a sustainable development. Solving EVCS-LRPTWRS involves periodic CS location selection multi-depot multi-period routing optimization. A bi-objective nonlinear programming model formulate minimum total operating cost number of EVs. hybrid algorithm combining Gaussian mixture clustering (GMCA) improved nondominated sorting genetic algorithm-II (INSGA-II) designed address EVCS-LRPTWRS. The GMCA employed assign customers appropriate various order reduce computational complexity. INSGA-II adopted obtain Pareto optimal solutions by using insertion operation select locations integrating elite retention mechanism ensure stable excellent performance. superiority proven comparison other three algorithms (i.e., multi-objective algorithm, particle swarm optimization, ant colony optimization). An empirical Chongqing City, China conducted. Then, four types period divisions scenarios modes further analyzed discussed. results demonstrate validity practicability solution method realizing distribution networks.