Robust Linear Programming
Robust Linear Programming is a mathematical optimization framework that extends linear programming by incorporating uncertainty in problem parameters, distinguishing itself through the incorporation of robustness constraints that ensure feasibility and optimality across all possible realizations within a defined uncertainty set.
196
Publications
23.6K
Citations
446
Authors
239
Institutions
Publications per year
2017–2026
67
196
Dimitris Bertsimas, Melvyn Sim · Operations Research · 2004 · 4.4K citations
Adjustable robust solutions of uncertain linear programs
Aharon Ben‐Tal, Alexander Goryashko, E. Guslitzer et al. · Mathematical Programming · 2004 · 1.4K citations
Adjustable robust solutions of uncertain linear programs
Ben-TalA., GoryashkoA., GuslitzerE. et al. · Mathematical Programming · 2004 · 859 citations
1–5 of 196
446
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7
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1–5 of 446
239
National University of Singapore
Singapore, Singapore
13 h-index
21 publications
3.2K citations
Massachusetts Institute of Technology
Cambridge, United States
11 h-index
14 publications
10.4K citations

UNSW Sydney
Sydney, Australia
9 h-index
19 publications
893 citations
Technion – Israel Institute of Technology
Haifa, Israel
7 h-index
13 publications
12.6K citations

Tilburg University
Tilburg, The Netherlands
5 h-index
11 publications
4.3K citations

North China Electric Power University
Beijing, China
4 h-index
6 publications
355 citations
Columbia University
New York, United States
4 h-index
7 publications
205 citations
Stanford University
Stanford, United States
4 h-index
4 publications
2.4K citations
1–8 of 239
16 publications · 5.6K citations
13
h-index
8 publications · 5.7K citations
8
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7 publications · 246 citations
7
h-index
6 publications · 639 citations
6
h-index
6 publications · 2.4K citations
6
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1–5