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A discussion on the conservatism of robust linear optimization problems

文献类型:期刊论文

作者Liu, Pengfei; Yang, Wenguo; Guo, Tiande
刊名Optimization
出版日期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
DOI10.1080/02331934.2016.1149710
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
WOS记录号WOS:000379619500010
出版者TAYLOR & FRANCIS LTD
URI标识http://www.irgrid.ac.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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来源:中国科学院大学

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