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	A discussion on the conservatism of robust linear optimization problems
	Liu, Pengfei; Yang, Wenguo; Guo, Tiande
刊名	Optimization
	2016
卷号	65期号:8页码:1641-1650
关键词	Robust approaches Conservatism Linear programming Combinatorial optimization
ISSN号	0233-1934
DOI	10.1080/02331934.2016.1149710
通讯作者	Yang, wenguo(yangwg@ucas.ac.cn)
英文摘要	In 2004, bertsimas and sim proposed a robust approach that can control the degree of conservatism by applying a limitation to the maximum number of parameters that are allowed to change. however, the robust approach can become extremely conservative even when is relatively small. in this paper, we provide a theoretical analysis to explain why this extreme conservatism occurs. we further point out that the robust approach does not reach an extremely conservative state when is less than k, where k is the number of nonzero components of the optimal solution of the extremely conservative robust approach. this research also shows that care must be taken when adjusting the value of to control the degree of conservatism because the approach may result in greater conservatism than was intended. we subsequently apply our analysis to additive combinatorial optimization problems. finally, we illustrate our results on numerical simulations.
WOS关键词	UNCERTAINTY ; PROGRAMS
WOS研究方向	Operations Research & Management Science ; Mathematics
WOS类目	Operations Research & Management Science ; Mathematics, Applied
语种	英语
出版者	TAYLOR & FRANCIS LTD
WOS记录号	WOS:000379619500010
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/2374690
专题	中国科学院大学
通讯作者	Yang, Wenguo
作者单位	Univ Chinese Acad Sci, Sch Math Sci, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Liu, Pengfei,Yang, Wenguo,Guo, Tiande. A discussion on the conservatism of robust linear optimization problems[J]. Optimization,2016,65(8):1641-1650.
APA	Liu, Pengfei,Yang, Wenguo,&Guo, Tiande.(2016).A discussion on the conservatism of robust linear optimization problems.Optimization,65(8),1641-1650.
MLA	Liu, Pengfei,et al."A discussion on the conservatism of robust linear optimization problems".Optimization 65.8(2016):1641-1650.

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