The Routing Problem for Electric Truck with Partial Nonlinear Charging and Battery Swapping

The maritime industry has introduced the concept of “green ports” as a means to achieve sustainable development by reducing carbon emissions. Within ports, trucks play crucial role in transportation operations. However, there is limited comprehensive research on electric truck routing problem containing practical constraints such charging options and processes. This study presents more realistic for trucks, with specific focus multiple within green ports. To address this challenge, we formulate mixed-integer programming model designed minimize overall operational costs associated over planning horizon. In order solve effectively, devise an Adaptive Large Neighborhood Search (ALNS) algorithm, embedded several customized operators. Through series numerical experiments, effectiveness proposed algorithm verified. experimental results provide compelling evidence superior performance compared original ALNS algorithm. Furthermore, sensitivity analysis conducted, leading valuable managerial insights.