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

Abstract

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