| 改进自适应遗传算法在函数优化中的应用研究 |
| |
| 引用本文： | 陈明杰,刘胜.改进自适应遗传算法在函数优化中的应用研究[J].哈尔滨工程大学学报,2007,28(8):875-879. |
| |
| 作者姓名： | 陈明杰 刘胜 |
| |
| 作者单位： | 1. 哈尔滨工业大学,控制科学与工程博士后流动站,黑龙江,哈尔滨,150001;哈尔滨工程大学自动化学院,黑龙江,哈尔滨,150001
2. 哈尔滨工程大学自动化学院,黑龙江,哈尔滨,150001 |
| |
| 基金项目： | 黑龙江省博士后科研启动基金
,
黑龙江省自然科学基金 |
| |
| 摘 要： | 为了改善传统自适应遗传算法的收敛速度以及局部收敛问题,根据种群适应度的集中程度,以种群的最大适应度、最小适应度以及适应度平均值这3个变量为基础,设计了改进的自适应交叉概率和变异概率来调整整个种群的交叉概率和变异概率,提出了一种基于种群适应度集中程度的改进自适应遗传算法.将该算法应用于函数优化中,仿真结果验证了其具有"快速收敛"的特点,且在很大程度上可避免遗传算法的早熟现象.
|
| 关 键 词： | 自适应遗传算法 交叉概率 变异概率 函数优化 全局收敛 |
| 文章编号： | 1006-7043（2007）08-0875-05 |
| 修稿时间： | 2006-08-18 |
An improved adaptive genetic algorithm and its application in function optimization |
| |
| CHEN Ming-jie,LIU Sheng.An improved adaptive genetic algorithm and its application in function optimization[J].Journal of Harbin Engineering University,2007,28(8):875-879. |
| |
| Authors: | CHEN Ming-jie LIU Sheng |
| |
| Abstract: | To speed up convergence rates and resolve local convergence issues in traditional adaptive genetic algorithms,an improved adaptive genetic algorithm was developed.According to the concentrating degree of fitness of the populations,a kind of adaptive crossover probability and mutation probability were designed in terms of three variables of maximal fitness,minimal fitness and average fitness of the populations,whereby the crossover probabilities and mutation probabilities of the whole populations could be adjusted.Based on this,an improved adaptive genetic algorithm was developed.Simulation results prove that the new adaptive algorithm can converge faster than the unimproved algorithm and is highly effective at avoiding the premature convergence of the adaptive genetic algorithm. |
| |
| Keywords: | adaptive genetic algorithm crossover probability mutation probability function optimization global convergence |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
|
