| 基于群体分类的自适应蚁群算法 |
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| 引用本文： | 荚恒松,毛力.基于群体分类的自适应蚁群算法[J].计算机工程与设计,2007,28(15):3668-3669,3689. |
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| 作者姓名： | 荚恒松 毛力 |
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| 作者单位： | 江南大学,信息工程学院,江苏,无锡,214122 |
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| 摘 要： | 针对基本蚁群算法在求解能力方面的不足,提出一种基于群体分类的自适应蚁群算法.该算法在智能蚁群的基础上引入随机蚁群以便扩大搜索空间,不同蚁群实行各自不同的搜索前进策略和信息更新机制,并可通过调节随机蚁群与智能蚁群的比例来控制收敛速度.多个旅行商问题的仿真实验证明,相比ACS、MMAX算法,该算法的求解能力得到了改进.
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| 关 键 词： | 蚁群算法 旅行商问题 随机蚁群 智能蚁群 自适应 体分类 自适应 蚁群算法 classification based 改进 验证 仿真 旅行商问题 收敛速度 控制 比例 调节 更新机制 信息 策略 前进 搜索空间 随机 智能 |
| 文章编号： | 1000-7024（2007）15-3668-02 |
| 修稿时间： | 2006-08-08 |
Self-adaptive ant colony algorithm based on classification |
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| JIA Heng-song,MAO Li.Self-adaptive ant colony algorithm based on classification[J].Computer Engineering and Design,2007,28(15):3668-3669,3689. |
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| Authors: | JIA Heng-song MAO Li |
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| Affiliation: | School of Information, Jiangnan University, Wuxi 214122, China |
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| Abstract: | To overcome the drawbacks of the conventional ant colony algorithm such as solution ability, a self-adaptive ant colony algorithm based on classification is proposed, The stochastic ant colony is introduced to extend the area of feasible solutions. Different ant colony has different mechanism of pheromone updating and the search strategy. The simulation results of several traveling salesman problems show that the proposed algorithm is feasible and highly efficient. |
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| Keywords: | ant colony algorithms traveling salesman problem stochastic ant colony intellective ant colony self-adaptive |
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