Robust Integer Programming
Robust Integer Programming is a mathematical optimization framework that belongs to the class of integer programming problems, distinguished by its explicit incorporation of uncertainty in problem parameters through robust optimization techniques to ensure feasible and optimal solutions under all realizations within a defined uncertainty set.
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5.2K
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196
Authors
117
Institutions
Publications per year
2017–2026
30
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Sayyad Nojavan, Behnam Mohammadi‐Ivatloo, Kazem Zare · IET Generation Transmission & Distribution · 2015 · 142 citations · Full text
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Kharazmi University
Tehran, Iran
4 h-index
8 publications
299 citations

Iran University of Science and Technology
Tehran, Iran
4 h-index
10 publications
220 citations
University of Florida
Gainesville, United States
3 h-index
8 publications
1.4K citations

University of Shanghai for Science and Technology
Shanghai, China
3 h-index
13 publications
551 citations
Intel (United States)
Santa Clara, United States
2 h-index
2 publications
36 citations

University of Tehran
Tehran, Iran
2 h-index
6 publications
258 citations
University of Southampton
Southampton, United Kingdom
2 h-index
3 publications
2.2K citations

École Nationale Supérieure de Techniques Avancées
Palaiseau, France
2 h-index
5 publications
2.8K citations
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4 publications · 390 citations
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4 publications · 707 citations
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OR · 3 publications · 1.1K citations
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ICCAD · 2 publications · 36 citations
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2 publications · 76 citations
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