一种改进的自适应遗传算法  

An Improved Adaptive Genetic Algorithm

作　　者：王庆飞[1] 贺兴时[1] 

机构地区：[1]西安工程大学理学院,陕西西安710048

出　　处：《甘肃联合大学学报（自然科学版）》2008年第5期69-71,共3页Journal of Gansu Lianhe University :Natural Sciences

摘　　要：针对传统遗传算法容易早熟及收敛速度慢的缺陷,提出了一种新的基于信息熵的遗传策略.该策略根据当前种群个体熵与种群熵的变化自适应调整遗传算子的各项参数,从而使得种群多样性得到保证,提高算法的全局搜索能力.试验结果表明了该方法在运行过程中能避免早熟的发生,在处理复杂问题时表现出较高的性能.To solve the problem of premature convergence and slow convergence flaws in the traditional genetic algorithm,a new genetic strategy which is based on information entropy is proposed. In this strategy, the algorithm will adaptively adjust its operator parameters in accordance with the current individual entropy and the population entropy. It ensures the diversity of the population and improve the global search capabilities. The result shows that this method can avoid the occurrence of premature convergence and provide excellent performance indealing complex problems.

关 键 词：遗传算法 函数优化 种群熵 早熟 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]