蜜蜂算法中受triz启发的不对称搜索邻域

S. Ahmad, D. Pham, K. Ng, M. Ang
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引用次数: 11

摘要

蜜蜂算法是一种模仿蜜蜂觅食行为的启发式优化程序,在群体智能研究中越来越受欢迎。该算法涉及邻域和全局搜索,能够找到复杂多模态优化问题的有希望的解决方案。邻域搜索的目的是加强对有希望的解的搜索,而全局搜索的目的是避免局部最优。通常,蜜蜂算法采用对称搜索邻域。与这种做法相反,在这项工作中尝试了一个受trz启发的不对称搜索邻域来探索邻域对称的意义。在一个工程设计问题上对该算法进行了不对称搜索邻域的验证。分析证实,在一定的不对称测量下,提出的算法产生了与蜜蜂算法相似的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
TRIZ-inspired Asymmetrical Search Neighborhood in the Bees Algorithm
The Bees Algorithm, a heuristic optimization procedure that mimics bees foraging behavior, is becoming more popular among swarm intelligence researchers. The algorithm involves neighborhood and global search and is able to find promising solutions to complex multimodal optimization problems. The purpose of neighborhood search is to intensify the search effort around promising solutions, while global search is to enable avoidance of local optima. Normally, a symmetrical search neighborhood is employed in the Bees Algorithm. As opposed to this practice, a TRIZ-inspired asymmetrical search neighborhood was tried in this work to explore the significance of neighborhood symmetry. The algorithm with an asymmetrical search neighborhood was tested on an engineering design problem. The analysis verified that under certain measurements of asymmetry, the proposed algorithm produced a similar performance as that of the Bees Algorithm.
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