Robust Duality is a theoretical framework in optimization that extends classical duality theory to robust optimization problems by establishing relationships between primal robust programs and their dual counterparts under uncertainty, ensuring dual feasibility and strong duality despite inexact or set-based parameter specifications.
116
Publications
13.7K
Citations
224
Authors
138
Institutions
Publications per year
2017–2026
43
Parents
Publications
116
1–5 of 116
Authors
224
- VJ
12
h-index
- GL
11
h-index
- XS
6
h-index
- AB
5
h-index
- DD
4
h-index
1–5 of 224
Institutions
138
UNSW Sydney
Sydney, Australia
11 h-index
23 publications
1K citations
Chongqing Technology and Business University
Chongqing, China
7 h-index
14 publications
349 citations
Pukyong National University
Busan, South Korea
5 h-index
7 publications
255 citations
Technion – Israel Institute of Technology
Haifa, Israel
5 h-index
8 publications
4.2K citations
Chongqing University
Chongqing, China
5 h-index
9 publications
319 citations
University of Alicante
Alicante, Spain
4 h-index
6 publications
236 citations
Tilburg University
Tilburg, The Netherlands
4 h-index
8 publications
2.1K citations
Massachusetts Institute of Technology
Cambridge, United States
4 h-index
8 publications
3.8K citations
1–8 of 138
Venues
- Journal of Optimization Theory and Applications
11 publications · 324 citations
10
h-index
- Mathematical Programming
7 publications · 590 citations
7
h-index
- Optimization
7 publications · 173 citations
7
h-index
- European Journal of Operational Research
6 publications · 1K citations
6
h-index
- SIAM Journal on Optimization
6 publications · 361 citations
6
h-index
1–5