摘要
文中针对函数优化方面遗传算法(GA)存在的"早熟"与收敛速度慢的问题,设计了一种基于交叉和变异算子改进的遗传算法。通过研究分析GA,根据交叉算子和变异算子的特点,在现有的GA基础上,引入拉普拉斯算子改进交叉算子以及结合黄金分割法对变异算子做了进一步改进。通过3个测试函数对该算法与标准遗传算法,以及其他两种算法加以对比,仿真结果表明文中的算法不仅增加了个体多样性,防止了"早熟",且比其他三种算法获得了更优解和更快的收敛速度。理论分析和实验表明,提出的算法是可行有效的。
Aiming at problems of genetic algorithm in terms of function optimization exists the ＂premature＂ and slow convergence, a kind of improved genetic algorithm based on crossover and mutation operators is designed. Through research and analysis of GA, according to the characteristics of the crossover operator and mutation operator, on the basis of existing GA, introduce the Laplacian operator to im- prove crossover operator and further improve nmtation operator combined with golden section method. Through the three test functions to compare this algorithm with standard Genetic Algorithm （GA）, and the other two algorithms, simulation results show that the proposed algorithm can not only increase the diversity of individuals, preventing the ＂premature＂, and more than the other three algorithms gain better solution and faster convergence. Theoretical analysis and experimental results show that the proposed method is feasible and effec- tive.
出处
《计算机技术与发展》
2014年第4期80-83,共4页
Computer Technology and Development
基金
广州市科技攻关项目(2012Y2-00040)
关键词
交叉算子
变异算子
优化
遗传算法
crossover operator
mutation operator
optimization
Genetic Algorithm （GA）
