| 基于分区策略的蚂蚁算法 |
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| 引用本文： | 于红斌,李孝安.基于分区策略的蚂蚁算法[J].微处理机,2007,28(3):78-80. |
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| 作者姓名： | 于红斌 李孝安 |
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| 作者单位： | 1. 河南师范大学计算机与信息技术学院,新乡,453007
2. 西北工业大学计算机学院,西安,710072 |
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| 基金项目： | 河南省科技攻关项目;河南师范大学校科研和教改项目;引进硕士课题启动费支持课题 |
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| 摘 要： | 蚂蚁算法是一种解决组合优化问题的有效算法,该算法具有许多优良的性质,但是也存在一些缺点,如计算时间较长等。该文在基本蚂蚁算法的基础上,提出分区策略和信息素直接优化策略。分区策略加快了蚂蚁算法初期信息素的获得速度,信息素直接优化方法加速了蚂蚁算法后期收敛的速度。实验表明,这种改进有效提高了蚂蚁算法的搜索效率。
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| 关 键 词： | 蚂蚁算法 分区策略 信息素 |
| 文章编号： | 1002-2279（2007）03-0078-03 |
| 修稿时间： | 2006-06-16 |
Ant Algorithm Based on Separating Areas Strategy |
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| YU Hong-Bin,LI Xiao-An.Ant Algorithm Based on Separating Areas Strategy[J].Microprocessors,2007,28(3):78-80. |
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| Authors: | YU Hong-Bin LI Xiao-An |
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| Abstract: | Ant algorithm(AA) is an effective algorithm to solve combinatorial problems which shows many promising characters,but it also has some shortcomings such as needing more computing time.Based on AA,two novel strategies are designed to improve the performance.One is separating the cities into several areas in order to obtain the initial pheromone more quickly.The other quickens the convergence rate by supposing pheromone direct optimization.Computing simulation experiments show its validity. |
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| Keywords: | Ant algorithm(AA) Separating areas strategy Pheromone |
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