| 基于群智能混合算法的物流配送路径研究 |
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| 引用本文： | 朱亚琪,方建安.基于群智能混合算法的物流配送路径研究[J].微型电脑应用,2012,28(10):1-4. |
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| 作者姓名： | 朱亚琪 方建安 |
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| 作者单位： | 1. 东华大学信息科学与技术学院自动化系 上海,201620
2. 东华大学信息科学与技术学院 上海,201620 |
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| 摘 要： | 针对物流车辆路径优化问题,考虑到基本蚁群算法有收敛速度慢、易陷入局部最优的缺点,采用了一种双种群蚁群算法,在蚁群的基础上引入差分进化(DE)和粒子群算法(PSO)。通过在PSOAS种群和DEAS种群之间建立一种信息交流机制,使信息能够在两个种群中传递,以免某一方因错误的信息判断而陷入局部最优点。通过matlab仿真实验测试,表明该群智能混合算法可以较好地解决TSP的问题。
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| 关 键 词： | 群智能混合算法 蚁群算法 差分进化算法 粒子群算法 TSP问题 |
Research on the Routing Problem in Logistics Distribution Based on Hybrid Algorithm of Swarm Intelligence |
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| Zhu Yaqi
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Fang Jianan.Research on the Routing Problem in Logistics Distribution Based on Hybrid Algorithm of Swarm Intelligence[J].Microcomputer Applications,2012,28(10):1-4. |
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| Authors: | Zhu Yaqi Fang Jianan |
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| Affiliation: | (College of Information Sciences and Technology, Donghua University, Shanghai 201620, China) |
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| Abstract: | Aiming at the drawbacks of slow convergence speed and being easy to fall into local optimal point for basic ant colony algorithm in logistics vehicle routing optimization issue, this paper adoptes a Dual Population Ant Colony Algorithm, Differential Evolution （DE） and Particle Swarm Optimization （PSO） is introduced on the basis of the ant colony. Through the establishment of an information exchange mechanism between PSOAS population and DEAS population, so that information can be passed in the two populations, so as not to be trapped in local minima due to wrong judgment. Matlab simulation experiment showes that the group of intelligent hybrid algorithm can solve the TSP problem. |
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| Keywords: | Hybrid Algorithm of Swarm Intelligence Ant Colony Algorithm Differential Evolution Particle Swarm Optimization TSP Problem |
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