基于模糊控制遗传算法的输电系统最优化规划

用遗传算法求解优化问题时，要花费大量时间对基因进行测试，，速度较慢。另外，遗传算法的性能还强烈地依赖于一睦相关参数（例如交叉和变异的概率）的选取。文中以电网规划为背景，对简单遗传算法（ＳＧＡ）进行了多方面改进，得到模糊控制遗传算法（ＦＬＣＧＡ）。该算法速度快，收敛到全局最优解的概率大。与基于传统遗传算法的电网规划比较，ＦＬＣＧＡ算有明显的优越性。

TRANSMISSION NETWORK PLANNING AND OPTIMIZATION MODEL WITH GENETIC ALGORITHMS BASED ON FUZZY LOGIC CONTROLLER

Genetic algorithms (GAs) provide a new strategy for global optimization. but the computation burden of theconventional GA is heavy. In this work, the simple genetic algorithm (SGA) is improved in many aspects in the context oftransmission network planning. and a heuristic--genetic algorithm is obtained. Moreover. a fuzzy logic controlled geneticalgorithm (FLCGA) is presented, in which two fuzzy logic controllers are implemented to adjust the crossover rate andmutation rate adaptively during the optimization process. In compare with SGA, the proposed FLCGA has much betterperformance, and can be applied to a wide range of system optimization and control problems.