Abstract
In order to minimize the distance of the Pareto front produced by Particle Swarm Optimization(PSO) with respect to the global Pareto front and maximize the spread of solutions found by PSO,a multi-objective particle swarm optimization based on crossover and mutation(CMMOPSO).In the CMMOPSO,firstly,the number of particle in sparse part of Pareto front was defined and the crossover operator was employed to increase the diversity of the nondominated solutions;next,the mutation operation was used for the particles far away from Pareto front to improve the probability to fly to Pareto front.In benchmark functions,CMMOPSO achieves better solutions than other algorithms.
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