Abstract: Based on Particle Swarm Optimization(PSO), effects of the major parameters are studied and the standard test functions are divided into two kinds. The setting of the acceleration coefficient for different functions and its cooperation with inertia weight in PSO algorithm are systematically investigated. It provides the evidence for further research and much help for application of PSO algorithm.

Key words: Particle Swarm Optimization(PSO), acceleration coefficient, inertia weight

摘要： 基于粒子群优化的原理，利用标准测试函数对粒子群算法的参数设计进行实验分析，依据函数特性进行初步分类，揭示不同类型优化问题中加速系数与惯性权重的相互关系及其设计规律。该项研究成果为粒子群算法的理论研究提供了实验依据，并为算法的实际应用创造了有利条件。

关键词: 粒子群优化, 加速系数, 惯性权重

CLC Number: 

• TP301.6