| 引用本文: | 喻学才,张田文.粒子群优化的多群蚂蚁算法[J].哈尔滨工业大学学报,2010,42(5):766.DOI:10.11918/j.issn.0367-6234.2010.05.021 |
| YU Xue-Cai,ZHANG Tian-wen.Multiple colony ant algorithm based on particle swarm optimization[J].Journal of Harbin Institute of Technology,2010,42(5):766.DOI:10.11918/j.issn.0367-6234.2010.05.021 |
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| 摘要: |
| 设计多蚁群算法的关键是群间的信息交换规则.利用粒子群优化中粒子移动的基本思想研究了蚁群间信息交换的新规则,定义了新的多蚁群优化算法.新算法的信息交换所占用的数据通信量要远低于现有的信息交换方法.将新算法用于求解带时间窗的车辆路由问题并和以前的最好的多蚁群算法做比较,计算结果表明:新算法的性能超过了已有的方法.采用群体智能中个体的移动思想来设计群间信息交换规则能改进多蚁群算法的求解性能. |
| 关键词: 蚁群优化 粒子群优化 带时间窗的车辆路由问题 |
| DOI：10.11918/j.issn.0367-6234.2010.05.021 |
| 分类号:TP18 |
| 基金项目: |
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| Multiple colony ant algorithm based on particle swarm optimization |
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YU Xue-Cai1,2, ZHANG Tian-wen2
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1.School of Computer Science and Technology,Harbin Institute of Technology,Harbin 150001,China;2.Transportation College,Zhejiang Normal University,Jinhua 321004,China)
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| Abstract: |
| This work suggested a new multi-ACO algorithm by introducing the basic idea in the particle swarm optimization(PSO) into solution information exchange between ant colonies.The new algorithm takes much less cost for exchanging solution information than those existing methods.The new algorithm was used to solve the VRPTW benchmark instances and was compared with one existing algorithm.The results show that the new algorithm out performs the existing methods.Exploiting the idea of individual moving in the swarm intelligence to design the rule of information exchange between ant colonies can improve the performance of multi-ACO algorithm. |
| Key words: ant colony optimization particle swarm optimization vehicle routing problem with time windows |
