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Cuckoo search with varied scaling factor 被引量:15
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作者 Lijin WANG Yilong YIN Yiwen ZHONG 《Frontiers of Computer Science》 SCIE EI CSCD 2015年第4期623-635,共13页
Cuckoo search (CS), inspired by the obligate brood parasitic behavior of some cuckoo species, iteratively uses L6vy flights random walk (LFRW) and biased/selective random walk (BSRW) to search for new solutions.... Cuckoo search (CS), inspired by the obligate brood parasitic behavior of some cuckoo species, iteratively uses L6vy flights random walk (LFRW) and biased/selective random walk (BSRW) to search for new solutions. In this study, we seek a simple strategy to set the scaling factor in LFRW, which can vary the scaling factor to achieve better performance. However, choosing the best scaling factor for each problem is intractable. Thus, we propose a varied scal- ing factor (VSF) strategy that samples a value from the range [0,1] uniformly at random for each iteration. In addition, we integrate the VSF strategy into several advanced CS vari- ants. Extensive experiments are conducted on three groups of benchmark functions including 18 common test functions, 25 functions proposed in CEC 2005, and 28 functions intro- duced in CEC 2013. Experimental results demonstrate the ef- fectiveness of the VSF strategy. 展开更多
关键词 cuckoo search algorithm uniform distribution random sampling scaling factor function optimization prob-lems
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