A Quantum-Behaved Multi-Objective Pelican Optimization Algorithm for Electric Vehicle Routing Problem with Time Window

With the nation's progress in energy conservation and emission reduction, electric vehicles have been widely adopted in the logistics industry. Consequently, the electric vehicle routing problem (EVRP) has emerged as a challenge for logistics operation management. A novel multi-objective optimization method for electric vehicle routing problem with time window (EVRPTW) is proposed in this paper, which aims to minimize distribution costs and maximize customer evaluation. Firstly, EVRPTW is modeled with considering logistics distribution costs, customer evaluation, and traffic conditions. Secondly, a multi-objective pelican optimization algorithm (MOPOA) is designed, it incorporates enhancements from the sine-cosine algorithm and quantum behavior. These strategies improve convergence and diversity of non-dominated solutions. Finally, through benchmark tests and empirical example, the superiority and effectiveness of the algorithm is verified. The suggested methodology for EVRPTW is able to plan the route well.