| 旅行商问题推广及其混合智能算法 |
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| 引用本文： | 陈冬华.旅行商问题推广及其混合智能算法[J].华东交通大学学报,2011,28(2):102-106. |
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| 作者姓名： | 陈冬华 |
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| 作者单位： | 华东交通大学基础科学学院,江西,南昌,330013 |
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| 摘 要： | 旅行商问题(TSP)是典型的NP-hard问题,是组合优化研究领域中的热点问题之一.全体旅行商问题(CTSP)是TSP的变形推广,它是比TSP更复杂的一个问题,而且有着广泛的应用.遗传算法(GA)具有随机全局搜索能力,但对于系统反馈信息利用能力差,且收敛慢,求解效率低.蚁群系统(ACS)算法具有并行全局搜索能力,且在很...
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| 关 键 词： | TSP CTSP 遗传算法 蚁群算法 混合智能算法 |
CTSP and Combined Intelligent Algorithm |
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| Chen Donghua.CTSP and Combined Intelligent Algorithm[J].Journal of East China Jiaotong University,2011,28(2):102-106. |
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| Authors: | Chen Donghua |
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| Institution: | Chen Donghua(School of Basic Sciences,East China Jiaotong University,Nanchang 330013,China) |
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| Abstract: | Traveling salesman problem（TSP）,a typical NP-hard problem,is one of the hot researching topics in the combined optimization area.It has already attracted many researchers from all areas.CTSP,a promotion of TSP deformation,is more complex than TSP,and has a wide range of applications.Genetic algorithm（GA） has the ability of conducting a stochastic global searching.However,using ability of feedback information is poor,convergence is slow,and its solving efficiency is low.Ant colony system（ACS） algorithm not only has the ability of parallel global searching,but also can avoid converging to a local minimal solution to possibility of stopping evolution.It lacks initial information and slow convergence.GA and ACS can be combined into CIA,which can be used to solve CTSP,having good properties of fully using information and fast convergence. |
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| Keywords: | TSP CTSP |
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