A survey of adjustable robust optimization

•Surveys the literature on applications of adjustable robust optimization.•Surveys theoretical and methodological aspects of adjustable robust optimization.•Guides practitioners on how to apply adjustable robust optimization methods.•Presents the advantages and limitations of the adjustable robust o...

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Vydané v:European journal of operational research Ročník 277; číslo 3; s. 799 - 813
Hlavní autori: Yanıkoğlu, İhsan, Gorissen, Bram L., den Hertog, Dick
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier B.V 19.09.2019
Predmet:
Adjustable robust optimization
Multistage decision making
Robust optimization
Semi-infinite programming
Semi-infinite programming
Adjustable robust optimization
Robust optimization
Multistage decision making
ISSN:0377-2217, 1872-6860
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Popis
Shrnutí:•Surveys the literature on applications of adjustable robust optimization.•Surveys theoretical and methodological aspects of adjustable robust optimization.•Guides practitioners on how to apply adjustable robust optimization methods.•Presents the advantages and limitations of the adjustable robust optimization. Static robust optimization (RO) is a methodology to solve mathematical optimization problems with uncertain data. The objective of static RO is to find solutions that are immune to all perturbations of the data in a so-called uncertainty set. RO is popular because it is a computationally tractable methodology and has a wide range of applications in practice. Adjustable robust optimization (ARO), on the other hand, is a branch of RO where some of the decision variables can be adjusted after some portion of the uncertain data reveals itself. ARO generally yields a better objective function value than that in static robust optimization because it gives rise to more flexible adjustable (or wait-and-see) decisions. Additionally, ARO also has many real life applications and is a computationally tractable methodology for many parameterized adjustable decision variables and uncertainty sets. This paper surveys the state-of-the-art literature on applications and theoretical/methodological aspects of ARO. Moreover, it provides a tutorial and a road map to guide researchers and practitioners on how to apply ARO methods, as well as, the advantages and limitations of the associated methods.
ISSN:0377-2217
1872-6860
DOI:10.1016/j.ejor.2018.08.031