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	Improve enhanced fireworks algorithm with differential mutation
	Yu, Chao ; Li, Junzhi ; Tan, Ying
	2014
英文摘要	Fireworks algorithm (FWA) is a newly proposed swarm intelligence algorithm, which is used to solve optimization problems. However, the interaction of fireworks in FWA is not sufficient. In this paper, the differential mutation operator is introduced to improve the interaction mechanism of enhanced FWA (EFWA), which is the latest version of FWA. Extensive experiments on 30 benchmark functions were conducted to test the performance of the new algorithm named enhanced fireworks algorithm with differential mutation (FWA-DM). Experimental results have shown that differential mutation operator is able to improve EFWA. ? 2014 IEEE.; EI; January; 264-269; 2014-January
语种	英语
出处	2014 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2014
DOI标识	10.1109/SMC.2014.6973918
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/423969]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Yu, Chao,Li, Junzhi,Tan, Ying. Improve enhanced fireworks algorithm with differential mutation. 2014-01-01.

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