| 粒子群与遗传算法的混合算法 |
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| 引用本文： | 阳琼芳1,孙如祥1,2. 粒子群与遗传算法的混合算法[J]. 华侨大学学报(自然科学版), 2015, 0(6): 645-649. DOI: 10.11830/ISSN.1000-5013.2015.06.0645 |
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| 作者姓名： | 阳琼芳1 孙如祥1 2 |
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| 作者单位： | 1. 广西职业技术学院 计算机与电子信息工程系, 广西 南宁 530226;2. 广西大学 计算机与电子信息学院, 广西 南宁 530004 |
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| 摘 要： | 针对粒子群算法直接用于求解离散旅行商优化问题会存在诸多困难,通过分析粒子群算法、遗传算法各自优缺点,将粒子群算法、遗传算法有效结合组成混合算法用于求解离散旅行商问题.混合的目的在于保持两种算法各自的优点,并有效地避免各算法原有的不足.对3个不同规模的巡回旅行商问题进行实验,结果表明:混合算法提升了算法的局部搜索能力.
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| 关 键 词： | 离散旅行商问题 遗传算法 粒子群算法 自适应 启发策略 |
Mixed Research on Particle Swarm Optimization and Genetic Algorithm |
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| YANG Qiongfang1,SUN Ruxiang1,' target="_blank" rel="external">2. Mixed Research on Particle Swarm Optimization and Genetic Algorithm[J]. Journal of Huaqiao University(Natural Science), 2015, 0(6): 645-649. DOI: 10.11830/ISSN.1000-5013.2015.06.0645 |
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| Authors: | YANG Qiongfang1,SUN Ruxiang1,' target=" _blank" rel=" external" >2 |
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| Affiliation: | 1. Department of Computer and Electronic Information Engineering, Guangxi Vocational and Technical College, Nanning 530226, China; 2. College of Computer and Electronic Information, Guangxi University, Nanning 530004, China |
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| Abstract: | There are many difficulties when particle swarm optimization is used directly to solve discrete travelling salesman problem(TSP)optimization problems. Therefore, we analyze the advantages and disadvantages of particle swarm optimization algorithm and genetic algorithm, and then mix them to be an effective algorithm to solve discrete TSP. The purpose of combination is to keep the original advantages of the two kinds of algorithms and to avoid the existing deficiencies. We conduct some experiments on the 3 TSP problems different scales. The result shows that the hybrid algorithm can highly improve the local search ability of algorithm. |
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| Keywords: | genetic algorithm particle swarm optimization algorithm self-adaptive heuristic strategy |
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