改进自适应差分进化算法求解难约束优化问题  

An improved self-adaptive differential evolution algorithm for difficult constrained optimization problems

作　　者：杨亦[1] 

机构地区：[1]湖南女子学院信息技术系,湖南长沙410004

出　　处：《中南林业科技大学学报》2011年第8期198-203,共6页Journal of Central South University of Forestry & Technology

摘　　要：基于自适应差分进化算法和简易罚函数法,提出一种用于求解难约束优化问题的改进自适应差分进化算法。针对Bump问题的仿真实验表明,新算法不仅求解精度超过大部分的约束求解算法,而且收敛速度快于基于差分进化的算法。An improved self-adaptive differential evolution algorithm was proposed for constrained optimization problems（COPs） based on self-adaptive differential evolution algorithm and simple penalty function method. The simulation testing results according to the Bump problem show that the solutions of the new algorithm was better than those of the algorithms in the almost exiting literature and the convergence speed of the new algorithm was faster than that of differential evolution.

关 键 词：自适应差分进化算法 差分进化算法 简单罚函数算子 约束优化问题 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]