Diploid hybrid Particle swarm optimization with differential evolution for Open Vehicle Routing Problem

To improve the performance of particle swarm optimization and differential evolution, the diploid differential evolution particle swarm optimization was presented according to the genetics rules. The algorithm was applied into the Open Vehicle Routing Problem. In the algorithm, dominant character and recessive character were included in every individual. Particle swarm optimization was implemented by dominant character, and differential evolution was implemented by recessive character. Dominant character was replaced by recessive character if its fitness was smaller than recessive character. A real number encoding method was presented and some heuristics were modified and improved the solution. The parameters of algorithm were analyzed in the experiment. And comparison with other algorithms in the literatures showed the proposed algorithm was effective.