嵌套式模糊自适应遗传算法  

Nested Fuzzy Adaptive Genetic Algorithm

作　　者：喻寿益[1] 邝溯琼[1] 

机构地区：[1]中南大学信息科学与工程学院,湖南长沙410083

出　　处：《控制工程》2010年第1期75-79,共5页Control Engineering of China

基　　金：国家自然科学基金资助项目(60574030);国家自然科学重点基金项目资助(60634020)

摘　　要：针对简单遗传算法(SGA)收敛速度慢和早熟收敛现象,将模糊逻辑理论应用于遗传算法,并采用两级嵌套的遗传算法,随主遗传算法GA1求解优化问题的进化进程用模糊控制的方法自适应地调整遗传算法的交叉概率和变异概率;利用另一个遗传算法GA2优化模糊规则库,实现了一种嵌套式模糊自适应遗传算法(NFAGA)。仿真结果表明,这种算法的全局搜索收敛速度和解的质量明显优于SGA和一般的自适应遗传算法(AGA)。To the disadvantages such as low convergence rate and premature phenomenon in simple genetic algorithms （SGA）, the fuzzy control method is applied into the genetic algorithms to realize a nested fuzzy adaptive genetic algorithm （NFAGA）. By using the fuzzy control method, the crossover probabilities and mutation probabilities of genetic algorithms are adjusted with the evolutional process of the main genetic algorithm GA1, and the fuzzy rules of the fuzzy controller is optimized by another genetic algorithm GA2. Simulation results show that the NFAGA＇s convergence rate and solution quality exceed SGA＇s and AGA＇sobviously in the global search.

关 键 词：嵌套遗传算法 模糊规则 交叉概率 变异概率 

分 类 号：TP27[自动化与计算机技术—检测技术与自动化装置]