摘要： 研究惯性权值对粒子群算法(PSO)收敛性的影响，在分析线性权值递减策略基础上，提出一种基于各粒子适应值的递减策略——FDIW。标准测试函数对比实验表明，该策略可以使粒子在搜索初期获得更好的多样性，从而使粒子具有更强的摆脱局部极值的能力，在搜索末期可以加快粒子收敛速度以提高PSO算法的性能。

关键词: 粒子群优化算法, 惯性权值, 递减策略, 适应值

Abstract: Inspired by studying the effect of inertia weight in convergence of Particle Swarm Optimization(PSO) and analyzing advantages and disadvantages of the existing Linear Decreasing Inertia Weight(LDIW), a new modified strategy for inertia weight is proposed based on fitness——FDIW. Comparative experiments of benchmark functions indicate that for most continuous optimization problems, FDIW has more varieties of the swarm at the early stages so that it can escape from local minimum more easily. FDIW can speed up the convergence of particles at the later stages to improve the performance of PSO.

Key words: Particle Swarm Optimization(PSO) algorithm, inertia weight, decreasing strategy, fitness

中图分类号: 

• TP301.6