基于改进Tent映射的自适应变尺度混沌粒子群算法  

An Improved Adaptive Chaos Particle Swarm Optimization Algorithm Based on Improved Tent Map

作　　者：李国晓[1] 韦世丹[1] 

机构地区：[1]广东水利电力职业技术学院,广东广州510635

出　　处：《水力发电》2017年第2期89-93,共5页Water Power

摘　　要：为改善标准粒子群优化算法本身存在的缺陷,引入种群混沌初始化方法、参数自适应调整策略、早熟判断机制以及基于改进Tent映射的变尺度混沌局部搜索方法对原有算法进行改进,提出一种基于改进Tent映射的自适应变尺度混沌粒子群算法(Improved Adaptive Chaos PSO,IACPSO)。多种高维Benchmark函数的计算结果表明,IACPSO算法在计算精度、优化稳定性及收敛速度方面均明显优于其他改进粒子群优化算法。In order to improve the defect of basic Particle Swarm Optimization algorithm, an Improved Adaptive Chaos Particle Swarm Optimization （IACPSO） algorithm based on improved Tent map is proposed herein, which including population chaos initialization method, adaptive parameter adjusting strategy, precocious judgment mechanism and mutative scale chaos local search based on improved Tent map. The results of some high-dimensional Benchmark functions show that the IACPSO algorithm is better than other improved PSO on computation accuracy, optimization stability and convergence speed.

关 键 词：粒子群优化算法 TENT映射 变尺度 混沌 自适应 

分 类 号：P301.6[天文地球—地球物理学]