模糊自适应参数调整的改进遗传算法  

The Improved Genetic Algorithm Based on Fuzzy Controller with Adaptive Parameter Adjustment

作　　者：罗梅[1] 贾志娟[2] 

机构地区：[1]天津工程师范学院计算机系,天津300222 [2]郑州师范学院信息技术系,河南郑州450044

出　　处：《微电子学与计算机》2010年第4期1-4,8,共5页Microelectronics & Computer

基　　金：国家自然科学基金项目(50275113)

摘　　要：为提高遗传算法的优化性能,构建了交叉及变异算子的模糊动态调整器,给出了参数调整过程、模糊逻辑控制器的执行策略及控制过程.采用标准的Benchmark测试函数比较了模糊控制器参数调整的遗传算法和简单遗传算法的性能,结果表明该算法求解精度高,优化效率高及进化代数少.For providing the optimizaiton performance of the genetic algorithm, the fuzzy dynamic regulator for mutation and crossover operators is constructed, the adjusting process of parameter is specified, and the implementing tactics as well as the controlling process are also provided in detail. The performances of the improved genetic algorithm and simple genetic algorithm are compared by the standard Benchmark testing function, the result indicate that the proposed method has many advantages such as higher optimization accuracy, higher optimization efficiency and fewer evolution steps.

关 键 词：遗传算法 模糊逻辑控制器 算子分析 自适应参数调整 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]