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Multi-objective Particle Swarm Optimization Algorithm Based on Crowding-density

Zhang Jian-Qiu, Xu Feng, Huang You-Rui


In order to improve the distribution of multi-objective PSO algorithm, crowding-density is introduced for the update of elite set. The basic idea is: First, the crowding-density of each individual in the group is calculated, then a partial order set is set up according to the objective function value and crowding-density and finally, individuals are selected from the partial order set according to the principle of proportional selection, and the elite set is updated. The convergence and distribution of improved algorithm are studied by means of numerical experiments, the results of which show that the convergence of improved algorithm is roughly equal with the conventional multi-objective particle swarm optimization algorithm, but the distribution of improved algorithm has been significantly improved.


Multi-objective optimization,PSO,crowding-density,distribution.

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