计算机工程与应用 ›› 2007, Vol. 43 ›› Issue (22): 44-46.
• 学术探讨 • 上一篇 下一篇
李菲菲1,姚 坤1,刘希玉2
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LI Fei-fei1,YAO Kun1,LIU Xi-yu2
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摘要: 受自然界共生现象的启发,将微粒群算法和协同进化相结合,提出了一种多微粒群协同进化算法。进化过程中,粒子不仅要与本子群的其他微粒交换信息,还要受其他子群体的影响。通过对三个标准函数优化的实验结果表明,此算法在一定程度上避免了陷入局部极值点并且提高了收敛精度。
关键词: 微粒群算法, 协同进化, 多微粒群协同进化算法
Abstract: Illumined by phenomenon of co-evolution in nature,particle swarm optimization is combined with co-evolution,a multi-particle swarm co-evolution algorithm is presented.In the process of evolution,particle not only exchanges information with other particles in its sub-swarm but also is influenced by other sub-swarms.By doing experiments on three benchmark functions,the results show that the algorithm avoids to trap into local optimum in a certain extent and improves the precision of convergence.
Key words: particle swarm optimization, co-evolution, multi-particle swarm co-evolution
李菲菲1,姚 坤1,刘希玉2. 一种多微粒群协同进化算法[J]. 计算机工程与应用, 2007, 43(22): 44-46.
LI Fei-fei1,YAO Kun1,LIU Xi-yu2. Multi-particle swarm co-evolution algorithm[J]. Computer Engineering and Applications, 2007, 43(22): 44-46.
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http://cea.ceaj.org/CN/Y2007/V43/I22/44