摘要
针对遗传算法收敛速度慢、容易"早熟"等缺点,结合模糊推理、模拟退火算法和自适应机制,提出一种改进的遗传算法——模糊自适应模拟退火遗传算法(FASAGA),并分析了该算法的性能和特点.实验研究表明,该算法比标准的遗传算法(SGA)具有更快的收敛速度和寻优效果.
Due to shortcomings of genetic algorithm that its convergence speed is slow and it is often premature convergence, an improved genetic algorithm, fuzzy adaptive simulated annealing genetic algorithm （FASAGA）, is presented by integrating fuzzy inference, simulated annealing algorithm and adaptive mechanism. Then the performance and the characteristic of this method are analyzed. Simulation results illustrate that FASAGA has better convergence speed and optimal results than standard genetic algorithm.
出处
《控制与决策》
EI
CSCD
北大核心
2009年第6期843-848,853,共7页
Control and Decision
基金
国家科技支撑计划项目(2007BAF13B03)
浙江省自然科学基金项目(Y1080776)
关键词
遗传算法
模糊控制
模拟退火
自适应
Genetic algorithm
Fuzzy control
Simulated annealing
Adaptive
