价值工程
價值工程
개치공정
VALUE ENGINEERING
2015年
20期
198-200
,共3页
粒子群算法%惯性因子%凹凸性%收敛
粒子群算法%慣性因子%凹凸性%收斂
입자군산법%관성인자%요철성%수렴
Particle Swarm Optimization%inertia weight%convexity%convergence
粒子群算法的惯性因子是算法中的一个重要的参数，目前的研究结果表明，惯性因子为减函数时算法的运行效果更为良好。文中提供了四种减函数作为惯性因子可以使用的算子，它们的凹凸性各有不同。对四个算例的数值仿真结果表明，表现最好的是惯性因子先上凸后下凸的PSO，惯性因子为下凸函数的PSO综合表现优于惯性因子为上凸函数的情况。
粒子群算法的慣性因子是算法中的一箇重要的參數，目前的研究結果錶明，慣性因子為減函數時算法的運行效果更為良好。文中提供瞭四種減函數作為慣性因子可以使用的算子，它們的凹凸性各有不同。對四箇算例的數值倣真結果錶明，錶現最好的是慣性因子先上凸後下凸的PSO，慣性因子為下凸函數的PSO綜閤錶現優于慣性因子為上凸函數的情況。
입자군산법적관성인자시산법중적일개중요적삼수，목전적연구결과표명，관성인자위감함수시산법적운행효과경위량호。문중제공료사충감함수작위관성인자가이사용적산자，타문적요철성각유불동。대사개산례적수치방진결과표명，표현최호적시관성인자선상철후하철적PSO，관성인자위하철함수적PSO종합표현우우관성인자위상철함수적정황。
Aimed to the efficiency changes of PSO caused by different inertia weight operators, some research and analysis had been done in this paper. The study showed that the inertia weight should decrease progressively if you want to expand the search region and assure the convergence of PSO. Four operators of inertia weight were proposed in this paper,their convexity were different with each other. The research about four examples showed that if the inertia weight operator was concave at first and then went to convex, the performance of corresponding PSO was best in all four circumstances, and the convex strategy performed better than concave strategy.
