SOP: parallel surrogate global optimization with Pareto center selection for computationally expensive single objective problems
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Publication:727388
DOI10.1007/s10898-016-0407-7zbMath1356.90136OpenAlexW2266445208WikidataQ59477362 ScholiaQ59477362MaRDI QIDQ727388
Taimoor Akhtar, Tipaluck Krityakierne, Christine A. Shoemaker
Publication date: 6 December 2016
Published in: Journal of Global Optimization (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s10898-016-0407-7
blackboxradial basis functionsresponse surfacemetamodelsimulation optimizationcomputationally expensivetabu
Related Items (4)
High-dimensional black-box optimization under uncertainty ⋮ A surrogate-based cooperative optimization framework for computationally expensive black-box problems ⋮ On the choice of the low-dimensional domain for global optimization via random embeddings ⋮ GOPS: efficient RBF surrogate global optimization algorithm with high dimensions and many parallel processors including application to multimodal water quality PDE model calibration
Uses Software
Cites Work
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