| 遗传算法的收敛性研究 |
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| 引用本文： | 屠昂燕,陈建成.遗传算法的收敛性研究[J].培训与研究,2008,25(2):49-51. |
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| 作者姓名： | 屠昂燕 陈建成 |
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| 作者单位： | [1]绍兴文理学院计算机系,绍兴312000 [2]浙江工业职业技术学院计算机系,绍兴312000 |
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| 摘 要： | 通过马尔可夫链方法,分析种群在解空间上概率分布情况以及收敛到最优解的概率,证明经典GA是不会收敛到最优解的,若在GA中保留每一代的最佳个体,则可以收敛到最优解。讨论全局收敛和过早收敛的原因,最后提出GA操作中应遵循的原则是改进GA搜索性能的关键。
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| 关 键 词： | 遗传算法 收敛性 马尔可夫链 早熟收敛现象 |
On Convergence of Genetic Algorithm |
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| TU Ang-yan,CHEN Jian-cheng.On Convergence of Genetic Algorithm[J].Training and Research-Journal of Hubei College of Education,2008,25(2):49-51. |
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| Authors: | TU Ang-yan CHEN Jian-cheng |
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| Institution: | TU Ang-yan CHEN Jian-cheng (1 Dept. of Computer, Shaoxing University, Shaoxing Zhejiang 312000, China; 2 Dept. of Computer, Zhejiang Industry Polytechnic College, Shaoxing Zhejiang 312000, China) |
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| Abstract: | Based on the methods of Markov chain, the probability distribution of populations over the solution space and the probability of converging to the optimal solution were analyzed. It proves that classic GA is not converge to the optimal solution until the GA retains the best individuals of every generation. After that, the reasons of global convergence and premature convergence are discussed. Finally that GA operations should be guided by the principles, which is the key of improving the search performance of GA, is proposed. |
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| Keywords: | genetic algorithm convergence Markov chain premature convergence |
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