李绍军, 王惠, 姚平经. 求解全局最优化的遗传(GA)-Alopex算法的研究[J]. 信息与控制, 2000, 29(4): 304-308,314.
引用本文: 李绍军, 王惠, 姚平经. 求解全局最优化的遗传(GA)-Alopex算法的研究[J]. 信息与控制, 2000, 29(4): 304-308,314.
LI Shao-jun, WANG Hui, YAO Ping-jing. STUDY OF GENETIC ALPOEX ALGORITHMS FOR SEEKING THE GLOBAL OPTIMIZATION[J]. INFORMATION AND CONTROL, 2000, 29(4): 304-308,314.
Citation: LI Shao-jun, WANG Hui, YAO Ping-jing. STUDY OF GENETIC ALPOEX ALGORITHMS FOR SEEKING THE GLOBAL OPTIMIZATION[J]. INFORMATION AND CONTROL, 2000, 29(4): 304-308,314.

求解全局最优化的遗传(GA)-Alopex算法的研究

STUDY OF GENETIC ALPOEX ALGORITHMS FOR SEEKING THE GLOBAL OPTIMIZATION

  • 摘要: 针对遗传算法爬山能力差的弱点,对传统遗传算法进行改进,提出了将遗传算法与Alopex(Algorithms of patter nextraction)算法相结合,结合在一起的混合算法充分发挥了两者的优越性,对典型函数的测试表明该算法提高了遗传算法的计算速度和计算精度.

     

    Abstract: Directed at the weak capacity of climbing hill of genetic algorithm, we improve the standard genetic algorithm. The hybrid algorithms of genetic algorithm and algorithm of pattern extraction were brought out. The algorithm sufficiently shows the advantages of the two algorithms. The results for test function show that hybrid algorithm improves the computing speed and computing precision of genetic algorithms.

     

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