A Parallel Approach of a Hybrid Particle Swarm Optimization Algorithm to Solve the Vehicle Routing Problem with Time Windows

摘要

This article presents, at a first instance, a hybrid Particle Swarm Optimization algorithm to solve the Vehicle Routing Problem with Time Windows. The union of the metaheuristic GRASP, the heuristic PFIH and a local search method characterizes the hybridization. At a second instance, is presented a parallel approach to the proposed algorithm. The parallelism concentrates in reducing the computational time consumed by the sequential version. The computational experiments were performed using the 56 Solomon's instances and the results obtained are compared to the best results known in literature. Finally, these results are discussed and statistically analyzed. It was possible to show success to the parallel algorithm developed.