Research on Electric Vehicle Routing for Bulky Waste Collection Based on Improved Adaptive Large Neighborhood Search Algorithm

In recent years, with the increasing adoption of electric vehicles (EVs) in waste collection systems, research on related vehicle routing optimization has garnered significant attention. However, existing studies predominantly focus on traditional fuel-powered vehicles, while constraints unique to EVs—such as limited driving range and charging requirements—further complicate the problem. This paper addresses the route optimization problem for electric vehicles in bulky waste collection. A route optimization model incorporating three-dimensional packing constraints is established. Feasible solutions are initially constructed using a Genetic Algorithm (GA), followed by refinement through an improved Adaptive Large Neighborhood Search (ALNS) algorithm. Enhanced destruction and repair operators are designed to simultaneously optimize charging station selection and the efficient spatial arrangement of bulky waste. Simulation experiments across multiple datasets validate the algorithm's feasibility. Results demonstrate that the proposed method effectively resolves charging demands during bulky waste collection and significantly reduces operational costs.