基于六模糊控制器的自适应遗传算法

6FLCs-based adaptive genetic algorithm

为了提高遗传算法对满意解的搜索和优化能力,采用基于模糊逻辑的自适应控制策略,提出了一种符号编码的自适应遗传算法。该算法可自动均衡搜索和优化关系,采用6个模糊控制器实现对选择、交叉、变异操作的动态参数组合控制。试验和理论分析表明,六模糊控制器的组合控制方式可以综合两模糊控制器或三模糊控制器独立控制的性能。对旅行商(TSP:TravelingSalesmanProblem)问题的求解结果表明:该算法在解决类似于TSP的组合优化问题时,具有比标准遗传算法更好的性能。

Adaptive control strategies based on fuzzy logic are used to enhance the GA(Genetic Algorithm)'s capability of exploration and optimization for satisfying solution. Fuzzy logic controllers have been built for inducing suitable exploration and optimization relationship throughout the run of GA automatically. The proposed symboliccoded AGA(Adaptive Genetic Algorithm) uses 6 fuzzy logic controllers (6FLCs) to control genetic operating parameters of selection, crossover and mutation dynamically. Experiments and theoretic analyses show that the combination control method of 6FLCs could combine the good behaviors of the 2FLCsbased AGA and the 3FLCsbased AGA as a whole. Experimental results of the TSP(Traveling Salesman Problem) demonstrate that the 6FLCsbased AGA is more efficient than a standard GA in solving combinatorial optimization problems which is similar to the TSP.