混沌遗传算法在函数优化中的应用  

Application of Hybrid Genetic Algorithm in function Optimization

作　　者：王允建[1] 江锋锁[1] 李钟侠[1] 

机构地区：[1]江西理工大学机电工程学院,江西赣州341000

出　　处：《兵工自动化》2005年第2期65-66,共2页Ordnance Industry Automation

摘　　要：基于混沌遗传算法(HGA)的函数优化,将混沌优化方法嵌入到GA中替代GA变异算子,以改善变异个体适应值,加快了算法收敛。其主要算子包括:编码方式、选择算子、交叉算子、变异算子及采用精英保留策略。该算法可求解非线性全局最优化问题,并通过大海捞针(NIH)等仿真试验得到验证。The function based on hereditary algorithm (HGA) of the Chaos is optimized, optimization the method of the Chaos is imbedded in the operator of GA to substitutes mutation, in order to improving the suiting value of individual, and accelerating algorithms. Its main operators include coding way, selecting operator, cross operator, mutation operator and adopting elites to keep the tactics. The optimizing issue of non-linear the overall situation is solved with the algorithm, and emulation tests was proved through looking for a needle in a bottle of hay.

关 键 词：遗传算法 函数优化 混沌变异 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]