Abstract
Particle swarm optimization (PSO) is an evolutionary metaheuristic inspired by the flocking behavior of birds, which has successfully been used to solve several kinds of problems. In this paper, we refer to capacitated vehicle routing problem (CVRP) as the object to research distribution routing optimistic problem within transportation and logistics. An improved discrete particle swarm optimization (DPSO), a variant of PSO, combined with iterated local search (ILS) method is proposed. During the search process, the improved algorithm can adaptively adjust flying time of particles with the evolutionary generations and ILS ensures that the particles escaped from the local minimum. The experimental results for partial benchmark problems showed that the better results can be obtained by the method.
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