Improved select space multi-objective particle swarm optimization

In this paper, an improved select space multi-objective particle swarm optimization was proposed based on the study on particle swarm optimization algorithm for solving multi-objective optimization. The method applied an improved quick sort method to construct the non-dominated solution set. The upper limit of the non-dominated solution select space was set. At the same time, the optimal solution set was conserved by the use of the external set. The crowding degree operator was used to guide the uniform distribution of the particles. The external set was updated by the use of the concept of Pareto dominance. The crossover operator and mutation operator were introduced in order to increase the diversity of particle swarm. The simulation results verified the validity of the method.