计算机科学 ›› 2011, Vol. 38 ›› Issue (3): 248-251.
• 人工智能 • 上一篇 下一篇
李咏梅,周永权,姚祥光
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LI Yong-mei,ZHOU Yong-quan,YAO Xiang-guang
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摘要： 利用人工鱼群算法的追尾思想并在过程中加入拥挤度因子，对人工萤火虫群算法进行了改进，提出了一种改进型人工萤火虫群算法，并将该算法用于多峰函数的优化问题。通过实验仿真及与其他算法进行的对比分析表明，改进后的人工萤火虫群算法在种群规模较小、迭代次数较少的情况下也可以精确捕获函数定义域内的所有峰值。
关键词: 人工萤火虫群算法，追尾行为，拥挤度因子，多峰函数优化
Abstract: To improve the glowworm swarm optimization, the behavior of follow of the artificial fish school algorithm and a swarm degree were used. The improved algorithm was used to optimise multi modal functions. The experiment resups show that the algorithm, with the smaller populations and the fewer number of iterations, can simultaneous capture multiple optima of several standard multimodal test function.
Key words: Glowworm swarm optimization, Behavior of follow, Swarm degree, Multimodal function optimization
李咏梅,周永权,姚祥光. 基于追尾行为的改进型人工萤火虫群算法[J]. 计算机科学, 2011, 38(3): 248-251. https://doi.org/
LI Yong-mei,ZHOU Yong-quan,YAO Xiang-guang. Improved Glowworm Swarm Optimization Based on the Behavior of Follow[J]. Computer Science, 2011, 38(3): 248-251. https://doi.org/
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