Chaotic artificial bee colony with elite opposition-based learning

被引:8
作者
Guo, Zhaolu [1 ]
Shi, Jinxiao [2 ]
Xiong, Xiaofeng [2 ]
Xia, Xiaoyun [3 ]
Liu, Xiaosheng [4 ]
机构
[1] JiangXi Univ Sci & Technol, Sch Sci, Inst Med Informat & Engn, Ganzhou 341000, Peoples R China
[2] JiangXi Univ Sci & Technol, Sch Sci, Ganzhou 341000, Peoples R China
[3] JiangXi Univ Sci & Technol, Sch Informat Engn, Ganzhou 341000, Peoples R China
[4] JiangXi Univ Sci & Technol, Sch Architectural & Surveying & Mapping Engn, Ganzhou 341000, Peoples R China
基金
中国国家自然科学基金;
关键词
artificial bee colony; ABC; chaotic local search; opposition-based learning; OBL; elite strategy; ALGORITHM; OPTIMIZATION; STRATEGY; SEARCH;
D O I
10.1504/IJCSE.2019.099076
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Artificial bee colony (ABC) algorithm is a promising evolutionary algorithm inspired by the foraging behaviour of honey bee swarm, which has obtained satisfactory solutions in diverse applications. However, the basic ABC often demonstrates insufficient exploitation capability in some cases. To address this concerning issue, a chaotic artificial bee colony with elite opposition-based learning strategy (CEOABC) is proposed in this paper. During the search process, CEOABC employs the chaotic local search to promote the exploitation ability. Moreover, the elite opposition-based learning strategy is utilised to exploit the potential information of the exhausted solution. Experimental results compared with several ABC variants show that CEOABC is a competitive approach for global optimisation.
引用
收藏
页码:383 / 390
页数:8
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