| 基于免疫单亲遗传算法在TSP中的应用 |
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| 引用本文： | 霍冰鹏,张栋波.基于免疫单亲遗传算法在TSP中的应用[J].晋城职业技术学院学报,2012,5(1):43-46. |
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| 作者姓名： | 霍冰鹏 张栋波 |
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| 作者单位： | 晋城职业技术学院,山西晋城,048026 |
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| 摘 要： | 基本遗传算法保持群体多样性的能力较差,所以经常在问题求解的过程中极易陷入局部最优解。根据生物的免疫原理和单亲遗传算法并结合最近邻域算法思想提出的一种改进算法———基于免疫单亲遗传算法（IPGA）。免疫遗传算法中的基因重组、免疫记忆以及免疫元动态等特性,这些特性有助于改进基本遗传算法群体多样性的保持能力。最后结合48个城市旅行商问题进行了求解,仿真结果表明,基于免疫单亲遗传算法具有更好的性能,相对于传统的遗传算法收敛速度提高了30%。
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| 关 键 词： | 单亲遗传算法 免疫算法 最近邻算法 旅行商问题 |
The Application of the Algorithm in TSP Based on Immune Monolepsis Algorithm |
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| HUO Bing-peng
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ZHANG Dong-bo.The Application of the Algorithm in TSP Based on Immune Monolepsis Algorithm[J].Journal of Jincheng Institute of Technology,2012,5(1):43-46. |
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| Authors: | HUO Bing-peng ZHANG Dong-bo |
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| Institution: | (Jincheng Institute of Technology,Jincheng,Shanxi 048026,China) |
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| Abstract: | The genetic algorithm has a comparatively limited capacity in maintaining the diversity of groups.So it is often easily trapped into partial optimal solution in the process of solving problems.According to the immune principle of biology and the monolepsis algorithm,an improved algorithm——IPGA(which is based on immune monolepsis algorithm)is proposed,combined with the nearest neighbor method.The immune genetic algorithm is characteristic of such features as gene recombination,immune memory and immune meta dynamic,which helps to improve the basic genetic algorithm’s capacity of maintaining the diversity of groups.The final solution is obtained from travelling salesman problems of 48 cities.The simulation results show that the immune genetic algorithm has better performance,and compared with the traditional GA,its performance has been increased by 30%. |
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| Keywords: | monolepsis algorithm immune algorithm nearest neighbor method TSP(Traveling Salesman Problem) |
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