| 遗传算法及其在TSP中的应用 |
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| 引用本文： | 房育栋 郝建忠. 遗传算法及其在TSP中的应用[J]. 华南理工大学学报(自然科学版), 1994, 22(3): 124-127 |
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| 作者姓名： | 房育栋 郝建忠 |
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| 作者单位： | 华南理工大学无线电与自动控制研究所 |
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| 摘 要： | 本文详述遗传算法的起源、实现、及应用和存在的问题。遗传算法是仿自然界的自然选择法则设计的。算法源于一群随机基因组，通过一定的适应性判决消除适应性低的基因组，保留适应性中等的和高的基因组；并在高适应性的基因组中，随机进行变异和组配，将基因组补足到恒定的数量，再进行适应性判决，一直到满足问题的要求。本文就此法做了中国旅行商题，实验效果非常满意，产生的结果比用Ｈｏｐｆｉｅｌｄ神经网络计算结果要好得多。
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| 关 键 词： | TSP 遗传算法 基因组 神经网络 |
GENETIC ALGORITHMS AND ITS APPRICATION TO TSP |
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| Fang Yudong, Hao Jianzhong, Yu Yinglin, Wen Yuhan. GENETIC ALGORITHMS AND ITS APPRICATION TO TSP[J]. Journal of South China University of Technology(Natural Science Edition), 1994, 22(3): 124-127 |
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| Authors: | Fang Yudong Hao Jianzhong Yu Yinglin Wen Yuhan |
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| Abstract: | A genetic algorithm and its originality, realization, application and its problems are studied in the paper. Genetic algorithms come from natural selection.Some groups of genetic are stochastically selected, and their fitness are calculated. The groups of genes with lower fitness is deleted, the one with higher or average fitness is remained. The variations and crossover combinations are stochastically done in the group with higher fitness, so that the number of the groups remain a constant, then go back tO recalculate the fitness. This algorithm is used in the Chinese TSP Problem, and get a satisfactory result. |
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| Keywords: | s: TSP genetic algorithms optimum algorithm natural selection genome neural networks |
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