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	Ordinal optimisation of genetic control parameters for flow shop scheduling
	Wang, L ; Zhang, L ; Zheng, DZ
	2010-05-06 ; 2010-05-06
关键词	genetic algorithm ordinal optimisation optimal computing budget allocation scheduling stochastic optimisation ALGORITHMS SIMULATION Automation & Control Systems Engineering, Manufacturing
中文摘要	Genetic algorithm (GA) has been widely applied to many non-polynomial hard optimisation problems, such as flow shop and job shop scheduling. It is well known that the efficiency and effectiveness of GA highly depend on its control parameters, but even setting suitable parameters often suffers from tedious trial and error. Currently, setting optimal parameters is still an open problem and one of the most important and promising areas for GA. In this paper, the determination of optimal GA control parameters with limited computational effort and total simulation replication constraint, namely, population size, crossover and mutation probabilities, is firstly formulated as a stochastic optimisation problem. Ordinal optimisation and optimal computing budget allocation are then applied to select the optimal GA control parameters while providing reasonable performance evaluation for hard flow shop scheduling problems. Lastly the effectiveness of the methodology is demonstrated by simulation results based on benchmarks.
语种	英语 ; 英语
出版者	SPRINGER LONDON LTD ; GODALMING ; SWEETAPPLE HOUSE CATTESHALL ROAD, GODALMING GU7 3DJ, SURREY, ENGLAND
内容类型	期刊论文
源URL	[http://hdl.handle.net/123456789/9058]
专题	清华大学
推荐引用方式 GB/T 7714	Wang, L,Zhang, L,Zheng, DZ. Ordinal optimisation of genetic control parameters for flow shop scheduling[J],2010, 2010.
APA	Wang, L,Zhang, L,&Zheng, DZ.(2010).Ordinal optimisation of genetic control parameters for flow shop scheduling..
MLA	Wang, L,et al."Ordinal optimisation of genetic control parameters for flow shop scheduling".(2010).

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