| 一种改进的遗传算法 |
| |
| 引用本文： | 李红军,覃仁超.一种改进的遗传算法[J].新乡师范高等专科学校学报,2003,17(2):31-34. |
| |
| 作者姓名： | 李红军 覃仁超 |
| |
| 作者单位： | 西南科技大学,计算机科学学院软件教研室,四川,绵阳,621002 |
| |
| 基金项目： | 西南科技大学青年预研基金,项目编号:05ZK023080 |
| |
| 摘 要： | 传统的遗传算法有2个严重的缺点,即不能有效地消除过早收敛现象以及在进化后期搜索效率较低。模拟退火算法是基于金属退火的机理而建立起来的1种全局最优化方法,它能够以随机搜索技术从概率的意义上找到目标函数的全局最小点。将遗传算法与模拟退火算法相结合,提出模拟退火遗传算法。实验结果表明,该算法在性能上有较大的改善。
|
| 关 键 词： | 遗传算法 模拟退火算法 随机搜索 模拟退火遗传算法 |
| 文章编号： | 1008-7613(2003)02-0031-04 |
| 修稿时间： | 2003年3月5日 |
Performance Appraisement of the Simulated Annealing Genetic Algorithms |
| |
| LI Hong-jun,QIN Ren-chao.Performance Appraisement of the Simulated Annealing Genetic Algorithms[J].Journal of Xinxiang Teachers College,2003,17(2):31-34. |
| |
| Authors: | LI Hong-jun QIN Ren-chao |
| |
| Abstract: | Traditional Genetic algorithm has two serious shortcomings , namely can't overcame and restrained the phenomenon for a long time effectively , and is evolving on later stage and searching for efficiency relatively low . Simulation anneal algorithm to set up a kind of the overall situation that stand up optimize the method most on the basis of mechanism that the metal anneals, It can be in order to search for small spot the most of the overall situation that technology finds the function of targets from meaning of probability at random. This text anneal genetic algorithm and simulation algorithm combine together, propose the simulated annealing genetic algorithm. The experimental result shows, there is greater improvement on performance in this algorithm. |
| |
| Keywords: | genetic algorithms simulated annealing search for at random the simulated annealing genetic algorithms |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
