| 蚁群系统自适应策略的改进与分析 |
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| 引用本文： | 李华锋,吴畏,丘一婷,钟柱亮,张军. 蚁群系统自适应策略的改进与分析[J]. 计算机工程, 2009, 35(18): 194-197 |
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| 作者姓名： | 李华锋 吴畏 丘一婷 钟柱亮 张军 |
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| 作者单位： | 中山大学计算机科学系,广州,510006 |
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| 摘 要： | 蚁群系统能够通过自适应调整不断优化算法的性能。为寻求算法自适应过程的内部规律，结合旅行商问题，采用参数控制、设置信息素范围的方法进行探讨。通过调控信息素的变化，以及对信息素最值、分布状态的统计分析，揭示算法优化过程的内部状态。实验表明，改进后的算法更稳定，问题解的搜索能力更强。
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| 关 键 词： | 蚁群系统 自适应 参数控制 信息素 旅行商问题 |
| 修稿时间： | |
Improvement and Analysis of Self-adaptive Strategy in Ant Colony System |
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| LI Hua-feng,WU Wei,QIU Yi-ting,ZHONG Zhu-liang,ZHANG Jun. Improvement and Analysis of Self-adaptive Strategy in Ant Colony System[J]. Computer Engineering, 2009, 35(18): 194-197 |
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| Authors: | LI Hua-feng WU Wei QIU Yi-ting ZHONG Zhu-liang ZHANG Jun |
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| Affiliation: | Department of Computer Science;Sun Yat-sen University;Guangzhou 510006 |
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| Abstract: | Ant Colony System(ACS) can develop excellent performance via self-adaptive behavior.In order to find the internal rules of self-adaptive behavior, this paper introduces parameter-control and sets pheromone's range, which are applied to the Traveling Salesman Problem(TSP).The ACS internal state is revealed via pheromone's micro-control and statistical analysis of pheromone's most values and distribution.Experimental results prove that the improved ACS does well in stability and searching solution. |
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| Keywords: | Ant Colony System(ACS) self-adaptive parameter-control pheromone Travelling Salesman Problem(TSP) |
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