A smoothed dynamic tabu search embedded GRASP for m-VRPTW

Vehicle routing problem with both time window and limited number of vehicles (m-VRPTW) is an useful extension of VRPTW problem in real applications. We propose an improved greedy randomized adaptive search procedure (GRASP) framework by techniques including multiple initialization and solution reuse. Furthermore, a new technique of smoothed dynamic tabu search is embedded into the GRASP to improve the performance. The experimental results for benchmark data show that the new algorithm can solve the m-VRPTW problem better than the published algorithm in accuracy.