Multi-objective route search for electric vehicles using ant colony optimization

In this paper, a temporal multi-objective ant colony optimization (ACO) algorithm is proposed to generate the routing plan for electric vehicles to fulfill the various requirements of drivers under a time-dependent stochastic traffic environment. The algorithm optimizes the route length, traveling time, energy, battery recycling lifetime and cabin temperature integrally, and meets constraints on arrival time and state of charge limitation. Simulation experiments are conducted and three different evaluation indexes are adopted. The performance of the algorithm is compared with two other multi-objective ACO methods. The proposed algorithm is proven to process higher convergence performance, and the solutions are also widely distributed, which suggests the effectiveness of this newly presented algorithm.