Electric Vehicle Routing Problem with Soft-Time Windows Considering Nonlinear Energy Consumption and Partial Recharge Strategies

Aiming at the problems of short driving range and difficult charging caused by limited battery capacity and charging equipment of electric vehicles, this paper constructs a route planning model of Electric Vehicle Routing Problem with soft-time windows considering nonlinear function and partial charging strategy. The goal is to minimize vehicle usage costs, transportation distance costs, charging time costs, and late time costs. An Adaptive Large Neighborhood Search (ALNS) algorithm with local search enhancement is designed to solve the problem. The optimization method of customer repair operators and route destroy operators are introduced into the algorithm, and the local search operator is used to further optimize. We then perform numerical experiments to verify the effectiveness of the algorithm on different scale examples, and finally study the effects of partial charging strategy and nonlinear energy consumption and charging on cost. This study can provide some theoretical support for the freight transportation of electric logistics vehicles.