| 求解TSP的改进遗传算法 |
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| 引用本文： | 谭宁波,王娇,牟廉明.求解TSP的改进遗传算法[J].佳木斯大学学报,2009,27(4):517-519. |
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| 作者姓名： | 谭宁波 王娇 牟廉明 |
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| 作者单位： | 谭宁波,牟廉明(内江师范学院数学与信息科学学院,四川,内江,641112);王娇(内江师范学院化学与生命科学学院,四川,内江,641112) |
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| 基金项目： | 内江师范学院大学生科研项目 |
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| 摘 要： | 遗传算法是求解旅行商问题的一种全局优化概率搜索算法方法,文中针对遗传算法较快的找到最优解并防止"早熟"收敛问题,提出了一种新的分级方法,该方法在各级中以群体当前最优个体替代各级中的最差个体,并在各级中采用自适应变异概率,改进后的遗传算法不但有效的维持了群体的多样性,而且提高了收敛速度,最后实验表明,改进的算法是可行和有效的.
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| 关 键 词： | 旅行商问题 遗传算法 分级 精英选择策略 |
Improved Genetic Algorithm for Solving TSP Problem |
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| TAN Ning-bo,WANG Jiao,MOU Lian-ming.Improved Genetic Algorithm for Solving TSP Problem[J].Journal of Jiamusi University(Natural Science Edition),2009,27(4):517-519. |
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| Authors: | TAN Ning-bo WANG Jiao MOU Lian-ming |
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| Institution: | 1.College of Mathematics and Information Science;Neijiang Normal University;Neijiang 641112;China;2.College of Chemistry and Life Science;China |
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| Abstract: | Genetic Algorithms for Traveling Salesman Problem is a global optimization method of the probability of search algorithm.In this paper,genetic algorithm was used to find optimal solutions faster and to prevent "premature" convergence problem.A new classification method that the worst individuals at all levels were replaced by the current best individual in groups was proposed,in which adaptive mutation probability was used for at all levels.The genetic algorithm not only effectively improved the diversity o... |
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| Keywords: | TSP genetic algorithm classification elitist selection strategy |
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