Multi-objective vehicle routing problem with time windows under uncertain conditions

In this paper, we research the multi-objective vehicle routing problem with time windows under uncertainty. For solving it efficiently, the robust multi-objective particle swarm optimization incorporates the simulated annealing algorithm is proposed. The new algorithm aims to improve the local search abilities of particles. Experimental results show that the proposed algorithm outperforms the traditional the robust multi-objective particle swarm optimization algorithm on the selected problem sets as the uncertain interference intensity increases.