| 求解物流配送问题的混合粒子群算法 |
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| 引用本文： | 胡文皓1,3,陈曙东2,3,辛欣1,3. 求解物流配送问题的混合粒子群算法[J]. 华侨大学学报(自然科学版), 2016, 0(3): 295-298. DOI: 10.11830/ISSN.1000-5013.2016.03.0295 |
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| 作者姓名： | 胡文皓1 3 陈曙东2 3 辛欣1 3 |
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| 作者单位： | 1. 中国科学院大学 电子电气与通信工程学院, 北京 100049;2. 中国科学院 微电子研究所, 北京 100029;3. 中国物联网研究发展中心, 江苏 无锡 214135 |
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| 摘 要： | 为了加快粒子群算法(PSO)在解决限定车辆配送问题时的收敛速度和减少时间花费,采取先验判断粒子个体最优位置与全局最优位置的距离决定粒子的更新方式,提出一种混合策略,设计鱼群-粒子群算法(AFSA-PSO),并通过对函数极值的求解进行验证.实验结果表明:该方法能够得到正确解,并具有收敛快、寻优佳的特点.
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| 关 键 词： | 粒子群算法 鱼群算法 混合算法 物流配送问题 |
Hybrid Particle Swarm Algorithm for the Logistics Distribution Problem |
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| HU Wenhao1,' target="_blank" rel="external">3,CHEN Shudong2,' target="_blank" rel="external">3,XIN Xin1,' target="_blank" rel="external">3. Hybrid Particle Swarm Algorithm for the Logistics Distribution Problem[J]. Journal of Huaqiao University(Natural Science), 2016, 0(3): 295-298. DOI: 10.11830/ISSN.1000-5013.2016.03.0295 |
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| Authors: | HU Wenhao1,' target=" _blank" rel=" external" >3,CHEN Shudong2,' target=" _blank" rel=" external" >3,XIN Xin1,' target=" _blank" rel=" external" >3 |
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| Affiliation: | 1. School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China; 2. Institute of Microelectronics, Chinese Academy of Sciences, Beijing 100029, China; 3. China Research and Development Center for Internet of Things, Wuxi 214135, China |
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| Abstract: | In order to speed up convergence and reduce the time, when using the particle swarm algorithm(PSO)to solve the limited vehicle distribution problem, we use the distance between the individual optimal position and the global optimal position to decide particle updating mode, and propose a hybrid improved strategy, then we design a new AFSA-PSO algorithm. Experimental results show that it can get correct solution and has the characteristics of fast convergence and good searching effect. |
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| Keywords: | particle swarm algorithm artificial fish swarm algorithm hybrid algorithm logistics and distribution problem |
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