A Hybrid Co-evolution Algorithm for Multi-Constraints Electric Vehicle Routing Optimization

Electric vehicles (EVs) are the primary means of transportation for urban logistics. The key of the EVs logistics distribution is to achieve the efficient routing optimization and charging arrangement. This paper considers an electric vehicle routing problem with time windows that takes the mileage cost and number of vehicles cost into account. An optimization algorithm based on the hybrid co-evolution mechanism is proposed to solve the problem. Specifically, the delivery scheme is initialized by the sand cat swarm optimization algorithm, and improved by discrete search and large neighborhood search. In addition, the elite individual migration mechanism is introduced to take advantage of the collaboration among the sand cat population, which improves the solution quality of the hybrid algorithm. Finally, the experiment results prove that the hybrid co-evolution algorithm has a better optimal solution to the multi-constrained electric vehicle routing problem.