Multi-objective particle swarm optimization algorithm based on crowding distance sorting and its application

 

کتابخانه الکترونیکی دیتا ساینس

شناسه: Article-22917

عنوان: Multi-objective particle swarm optimization algorithm based on crowding distance sorting and its application

لینک: http://en.cnki.com.cn/Article_en/CJFDTOTAL-JSJJ200807010.htm

زبان: چینی

قیمت: 1,900 تومان 

Aiming at shortcomings in global searching capacity and diversified Pareto set existing in the traditional multi-objective particle swarm optimization algorithms,a multi-objective particle swarm optimization algorithm based on crowding distance sorting was proposed.With the elitism strategy,the shrink of the external population and update of the global optimum were achieved based on individuals’ crowding distance sorting in descending order.A small ratio mutation was introduced to the inner swarm to enhance the global searching capacity of the algorithm.And the number of Pareto optimal solutions could be controlled,the convergence and diversity of Pareto optimal set could be guaranteed as well.Effectiveness of the algorithm with two or three objectives was proved by the optimization of elevator traction performances.Comparison results among cases with different scales illustrated that this algorithm outperformed Strength Pareto Evolutionary Algorithm 2(SPEA2) in the convergence and diversity characteristics of Pareto optimal front with shorter computation time,higher efficiency and robustness.

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