摘要
为改善多目标粒子群算法的收敛性和多样性,通过对粒子群算法全局极值和个体极值选取方式的研究,采用随机选取和评估选取相结合的方法选取全局极值和个体极值,提出了一种可用于解决多目标优化问题的粒子群优化算法,从而实现了对多目标优化问题的非劣最优解集的搜索,仿真实验结果证明算法是有效的。
To improve the multi-objective particle swarm optimization algorithm convergence and diversity, Through the improvement of the option modes of gBest and pBest of PSO algorithm,by means of random selection and evaluation method of combining the selected selecting gBest and pBest, an optimization algorithm applied to solving multi-objective optimization problems is presented, and the search for Pareto optimal set of multi-objective optimization problems is implemented, the simulation experimental results have proved that the algorithm is effective.
出处
《电子设计工程》
2013年第3期36-39,共4页
Electronic Design Engineering
关键词
粒子群优化算法
多目标优化
评估选取
非劣最优解
particle swarm optimization
multi-objective optimization
selection evaluation
pareto optimal
