Umbrellalike Hierarchical Artificial Bee Colony Algorithm

作     者：Zheng, Tao Zhang, Han Zhang, Baohang Cai, Zonghui Wang, Kaiyu Todo, Yuki Gao, Shangce 

作者机构：Univ Toyama Fac Engn Toyama 9308555 Japan Kanazawa Univ Fac Elect Informat & Commun Engn Kanazawa 9201192 Japan 

出 版 物：《IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS》 (IEICE Trans Inf Syst)

年 卷 期：2023年第E106D卷第3期

页      面：410-418页

核心收录：

学科分类：0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Japan Society for the Promotion of Science (JSPS) KAKENHI [JP22H03643] Japan Science and Technology Agency (JST) Support for Pioneering Research Initiated by the Next Generation (SPRING) [JPMJSP2145] JST through the Establishment of University Fellowships to- wards the Creation of Science Technology Innovation [JPMJFS2115] Grants-in-Aid for Scientific Research [23K24899, 22H03643] Funding Source: KAKEN 

主　　题：population structure umbrellalike hierarchical information layer evolutionary algorithms 

摘      要：Many optimisation algorithms improve the algorithm from the perspective of population structure. However, most improve-ment methods simply add hierarchical structure to the original population structure, which fails to fundamentally change its structure. In this pa-per, we propose an umbrellalike hierarchical artificial bee colony algorithm (UHABC). For the first time, a historical information layer is added to the artificial bee colony algorithm (ABC), and this information layer is allowed to interact with other layers to generate information. To verify the effective-ness of the proposed algorithm, we compare it with the original artificial bee colony algorithm and five representative meta-heuristic algorithms on the IEEE CEC2017. The experimental results and statistical analysis show that the umbrellalike mechanism effectively improves the performance of ABC.