Summary: Recently proved successful for variants of the vehicle routing problem (VRP) involving time windows, genetic algorithms have not yet shown to compete or challenge current best search techniques in solving the classical capacitated VRP. In this paper, a hybrid genetic algorithm to address the capacitated vehicle routing problem is proposed. The basic scheme consists in concurrently evolving two populations of solutions to minimize total traveled distance using genetic operators combining variations of key concepts inspired from routing techniques and search strategies used for a time-variant of the problem to further provide search guidance while balancing intensification and diversification. Results from a computational experiment over common benchmark problems report the proposed approach to be very competitive with the best-known methods.
For the entire collection see [Zbl 1025.68696].