| 混合遗传算法与模拟退火法 |
| |
| 引用本文： | 田东平,迟洪钦.混合遗传算法与模拟退火法[J].计算机工程与应用,2006,42(22):63-65. |
| |
| 作者姓名： | 田东平 迟洪钦 |
| |
| 作者单位： | 上海师范大学数理信息学院,上海,200234 |
| |
| 摘 要： | 论文将适合全局搜索的遗传算法(GA)和适合局部搜索的模拟退火算法(SA)相结合,提出了混合GA-SA计算方法。一方面,算法采用混沌初始化,提高了初始群体的质量;另一方面,算法采用Gray编码以及动态自适应调节交叉概率和变异概率,提高了收敛速度,并有效防止种群早熟现象。实例验证了该算法的可行性和有效性。
|
| 关 键 词： | 遗传算法 模拟退火算法 混沌初始化 Gray编码 |
| 文章编号： | 1002-8331-（2006）22-0063-03 |
| 收稿时间： | 2005-11 |
| 修稿时间： | 2005-11 |
Hybrid Genetic Algorithm and Simulated Annealing |
| |
| Tian Dongping,Chi Hongqin.Hybrid Genetic Algorithm and Simulated Annealing[J].Computer Engineering and Applications,2006,42(22):63-65. |
| |
| Authors: | Tian Dongping Chi Hongqin |
| |
| Affiliation: | Mathematics and Sciences College,Shanghai Normal University,Shanghai 200234 |
| |
| Abstract: | This paper puts forward hybrid GA-SA by combining Genetic Algorithm(GA) and Simulated Annealing(SA)together,in which the former is suitable for global searching and the latter is suitable for local searching.In this paper,On the one hand,chaos intialization is adopted in order to improve the quality of initial population.On the other hand,Gray coding and dynamic adaptive probability of crossover and mutation are adopted,which can improve the evolution speed and prevent the population from premature.Four examples show that the hybrid GA-SA is feasible and effective. |
| |
| Keywords: | Genetic Algorithm(GA) Simulated Annealing(SA) chaos intialization Gray coding |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
|
