| 基于变区域搜索的改进遗传算法研究 |
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| 引用本文： | 汪金龙,朱亚军,薛云灿. 基于变区域搜索的改进遗传算法研究[J]. 九江医学, 2006, 21(3): 8-11 |
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| 作者姓名： | 汪金龙 朱亚军 薛云灿 |
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| 作者单位： | 九江学院电子工程学院,江西九江,332005;河海大学计算机及信息工程学院,江苏常州,213022 |
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| 摘 要： | 针对基本遗传算法容易陷入局部最优解的缺点,提出了一种求解全局最优解的变区域搜索遗传算法。该算法以上一代最优解为导向,在它所在的随机局部区域内搜索,以提高当代最优解附近的搜索密度,加快遗传算法的收敛速度。基于标准函数的仿真测试研究表明,本算法能有效地减小进化代数和提高最优解的精度,尤其适合维数较多的函数寻优。
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| 关 键 词： | 改进遗传算法 全局优化 变区域搜索 粒子群优化算法 |
| 文章编号： | 1006-3838（2006）03-0008-（03） |
| 收稿时间： | 2006-05-09 |
| 修稿时间： | 2006-05-09 |
AN IMPROVED GENETIC ALGORITHM BASED ON SPACE-VARIED SEARCHING |
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| JIANG Jin-Long,ZHU Ya-Jun,XUE Yun-Can. AN IMPROVED GENETIC ALGORITHM BASED ON SPACE-VARIED SEARCHING[J]. Jiujiang Medical Journal, 2006, 21(3): 8-11 |
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| Authors: | JIANG Jin-Long ZHU Ya-Jun XUE Yun-Can |
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| Affiliation: | 1. Faculty of Electronic Industry and Engineeing, Jiujiang University, Jiujiang 332005, China; 2 College of Computer and Information Eng., Hohai University, Changzhou, 213022 |
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| Abstract: | To overcome the premature convergence disadvantage of the basic genetic algorithms,an improved genetic algorithm based on varying-space searching is proposed to search for the global optimization solution. Guided by the best individual of the last generation.This improved algorithm searches better individuals in its local space.This enhances its search density near the local optimization solution and accelerates its convergence speed.Simulations are carried out on the standard test functions and the results show that the improved algorithm can find the global optimization and overcome the premature convergence efficiently,specially in functions of many dimensions. |
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| Keywords: | improved genetic algorithms global optimization varying-space search the direct search method Particle Swarm Optimization. |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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