Interpolation-based Optimization
Interpolation-Based Optimization is a derivative-free optimization method that constructs and iteratively updates a surrogate model by fitting interpolating functions to sampled function values, distinguishing itself through the exact matching of these values at observed points to guide the search for optimal solutions.
160
Publications
9.2K
Citations
412
Authors
223
Institutions
Publications per year
2017–2026
39
Parents
160
Global optimization using special ordered sets
E. M. L. Beale, J. J. H. Forrest · Mathematical Programming · 1976 · 277 citations
Fengwen Wang, Boyan S. Lazarov, Ole Sigmund et al. · Computer Methods in Applied Mechanics and Engineering · 2014 · 264 citations
Engineering, Computational Engineering, Mechanical Engineering +17
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223
Argonne National Laboratory
Lemont, United States
4 h-index
5 publications
213 citations
Purdue University West Lafayette
West Lafayette, United States
3 h-index
7 publications
88 citations

McMaster University
Hamilton, Canada
3 h-index
6 publications
297 citations

Beijing University of Chemical Technology
Beijing, China
3 h-index
12 publications
646 citations
University of Cambridge
Cambridge, United Kingdom
3 h-index
3 publications
301 citations

Cornell University
Ithaca, United States
3 h-index
4 publications
623 citations
Stanford University
Stanford, United States
3 h-index
4 publications
141 citations
University of Chinese Academy of Sciences
Beijing, China
2 h-index
4 publications
302 citations
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7 publications · 218 citations
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5 publications · 217 citations
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4 publications · 535 citations
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4 publications · 606 citations
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MCOM · 3 publications · 71 citations
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