Randomized Optimization Algorithms
Randomized Optimization Algorithms is a class of optimization algorithms that belong to the broader category of optimization methods, distinguished by the deliberate incorporation of randomness in their search or update mechanisms to improve efficiency, escape local optima, or handle uncertainty in the objective function or constraints.
217
Publications
13.1K
Citations
490
Authors
247
Institutions
Publications per year
2017–2026
59
Parents
217
Probabilistic approximation of metric spaces and its algorithmic applications
Y. Bartal · 2002 · 656 citations
Boosting combinatorial search through randomization
Carla P. Gomes, Bart Selman, Henry Kautz · 1998 · 565 citations
1–5 of 217
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Institute of Electronics, Computer and Telecommunication Engineering, Italy
6 publications · 221 citations
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1–5 of 490
247
Politecnico di Torino
Turin, Italy
9 h-index
16 publications
819 citations
Institute of Electronics, Computer and Telecommunication Engineering
Turin, Italy
8 h-index
12 publications
641 citations
University of California, Berkeley
Berkeley, United States
7 h-index
15 publications
860 citations
University of Maryland, College Park
College Park, United States
6 h-index
13 publications
529 citations
ETH Zurich
Zurich, Switzerland
6 h-index
18 publications
738 citations
Tokyo Institute of Technology
Tokyo, Japan
6 h-index
6 publications
349 citations

Centre National de la Recherche Scientifique
Paris, France
5 h-index
7 publications
168 citations
Stanford University
Stanford, United States
5 h-index
8 publications
978 citations
1–8 of 247
8 publications · 378 citations
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7 publications · 1.1K citations
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6 publications · 253 citations
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Conference · 5 publications · 131 citations
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Repository · 5 publications · 109 citations
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