蜜蜂算法
群体智能
觅食
局部搜索(优化)
计算机科学
搜索算法
启发式
数学优化
人工智能
群体行为
元启发式
算法
粒子群优化
数学
生态学
生物
作者
Siti Azfanizam Ahmad,Duc Truong Pham,Kok Weng Ng,Mei Choo Ang
摘要
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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