Energy Saving-Oriented Multi-Depot Vehicle Routing Problem with Time Windows in Disaster Relief

This paper studies the distribution of emergency relief for electric vehicles (EVs), which considers energy saving, multi-depot, and vehicle routing problems with time windows, named saving-oriented multi-depot problem windows (ESMDVRPTW). Our aim is to find routes EVs such that all shelter demands are fulfilled during their total cost traveled by fleet minimized. To this end, we formulate ESMDVRPTW as a mixed-integer linear programming model. Since post-disaster transportation network contains large number vertices arcs composed vertices, propose two-stage approach solve ESMDVRPTW. The first stage obtain minimal travel between any two in real-time on using proposed Floyd algorithm combined neighboring list (Floyd-NL algorithm). In second stage, develop genetic (GA) incorporating neighborhood search (GA-LNS), determines delivery scheme shelters. Simulation results MDVRPTW benchmark illustrate performance GA-LNS better than GA, simulated annealing (SA) tabu (TS). Finally, case constructed real cases acquired from OpenStreetMap (OSM) generated Quantum Geographic Information System (QGIS) Ichihara city, Japan, test show effectiveness approach.