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	A fast evolutionary algorithm for dynamic bi-objective optimization problems
	Liu, Min , ; Zeng, Wenhu ; Liu M(刘敏) ; Ceng WH(曾文华)
	2012
关键词	Computer science Education computing Engineering education Multiobjective optimization Search engines
英文摘要	Conference Name:2012 7th International Conference on Computer Science and Education, ICCSE 2012. Conference Address: Melbourne, VIC, Australia. Time:July 14, 2012 - July 17, 2012.; University of Melbourne; Many real-world optimization problems involve multiple objectives, constraints, and parameters which constantly change with time. In this paper, we suggest a fast dynamic bi-objective evolutionary algorithm (DBOEA). Specifically, a fast bi-objective non-dominated sorting is introduced to reduce the cost of the layering of non-dominated fronts. A differential evolution operator is also adopted as the new evolutionary search engine so as to accelerate the optimization search speed and improve the obtained results. The DBOEA is very fit for dynamic bi-objective optimization, for its computational complexity is O(NlogN). The simulate results demonstrate that the proposed DBOEA outperforms the well-known dynamic non-dominated sorting algorithm II (DNSGA-II) not only in running speed, but also in terms of finding a diverse set of solutions and in converging near the dynamic Pareto optimal front. 漏 2012 IEEE.
语种	英语
出处	http://dx.doi.org/10.1109/ICCSE.2012.6295042
出版者	IEEE Computer Society
内容类型	其他
源URL	[http://dspace.xmu.edu.cn/handle/2288/85334]
专题	海洋环境－会议论文
推荐引用方式 GB/T 7714	Liu, Min ,,Zeng, Wenhu,Liu M,et al. A fast evolutionary algorithm for dynamic bi-objective optimization problems. 2012-01-01.

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