Elite Opposition-based Artificial Bee Colony Algorithm for Global Optimization
محل انتشار: ماهنامه بین المللی مهندسی، دوره: 28، شماره: 9
سال انتشار: 1394
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 364
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شناسه ملی سند علمی:
JR_IJE-28-9_003
تاریخ نمایه سازی: 15 آذر 1394
چکیده مقاله:
Numerous problems in engineering and science can be transformed into optimization problems. Artificial bee colony (ABC) algorithm is a newly developed stochastic optimization algorithm and has been successfully used in many areas. However, due to the stochastic characteristics of the solution search equation, the traditional ABC algorithm often suffers from poor exploitation. Aiming at this weakness of the traditional ABC algorithm, in this paper, we propose an enhanced ABC algorithm with elite opposition-based learning strategy (EOABC). In the proposed EOABC, it executes the elite opposition-based learning strategy with a preset learning probability to enhance the exploitation capacity. In the experiments, EOABC is tested on a set of numerical benchmark test functions, and is compared with some other ABC algorithms. The comparisons indicate that EOABC can obtain competitive results on the majority of the test functions
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نویسندگان
z guo
School of Science, JiangXi University of Science and Technology, Ganzhou, China
s wang
School of Information Engineering, Shijiazhuang University of Economics, Shijiazhuang, China
x yue
School of Science, JiangXi University of Science and Technology, Ganzhou, China
d jiang
State Key Laboratory of Software Engineering, School of Computer, Wuhan University, Wuhan, China