Quantifying uncertainty on Pareto fronts with Gaussian process conditional simulations
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DOI: 10.1016/j.ejor.2014.07.032
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References listed on IDEAS
- Kleijnen, Jack P.C. & Mehdad, Ehsan, 2014. "Multivariate versus univariate Kriging metamodels for multi-response simulation models," European Journal of Operational Research, Elsevier, vol. 236(2), pages 573-582.
- Kleijnen, Jack P.C. & Mehdad, E., 2014.
"Multivariate Versus Univariate Kriging Metamodels for Multi-Response Simulation Models (Revision of 2012-039),"
Discussion Paper
2014-012, Tilburg University, Center for Economic Research.
- Kleijnen, Jack P.C. & Mehdad, E., 2014. "Multivariate Versus Univariate Kriging Metamodels for Multi-Response Simulation Models (Revision of 2012-039)," Other publications TiSEM 8a096696-f700-4cbe-9474-c, Tilburg University, School of Economics and Management.
- Roustant, Olivier & Ginsbourger, David & Deville, Yves, 2012. "DiceKriging, DiceOptim: Two R Packages for the Analysis of Computer Experiments by Kriging-Based Metamodeling and Optimization," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 51(i01).
- Bachoc, François, 2013. "Cross Validation and Maximum Likelihood estimations of hyper-parameters of Gaussian processes with model misspecification," Computational Statistics & Data Analysis, Elsevier, vol. 66(C), pages 55-69.
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Cited by:
- Capitanescu, F. & Marvuglia, A. & Benetto, E. & Ahmadi, A. & Tiruta-Barna, L., 2017. "Linear programming-based directed local search for expensive multi-objective optimization problems: Application to drinking water production plants," European Journal of Operational Research, Elsevier, vol. 262(1), pages 322-334.
- Dawei Zhan & Huanlai Xing, 2020. "Expected improvement for expensive optimization: a review," Journal of Global Optimization, Springer, vol. 78(3), pages 507-544, November.
- Carine M. Rebello & Márcio A. F. Martins & Daniel D. Santana & Alírio E. Rodrigues & José M. Loureiro & Ana M. Ribeiro & Idelfonso B. R. Nogueira, 2021. "From a Pareto Front to Pareto Regions: A Novel Standpoint for Multiobjective Optimization," Mathematics, MDPI, vol. 9(24), pages 1-21, December.
- Christophette Blanchet-Scalliet & Céline Helbert & Mélina Ribaud & Céline Vial, 2019. "Four algorithms to construct a sparse kriging kernel for dimensionality reduction," Computational Statistics, Springer, vol. 34(4), pages 1889-1909, December.
- Mayank Bajpai & Shreyansh Mishra & Shishir Gaur & Anurag Ohri & Hervé Piégay & Didier Graillot, 2022. "Optimization of Groundwater Pumping and River-Aquifer Exchanges for Management of Water Resources," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(6), pages 1863-1878, April.
- Rivier, M. & Congedo, P.M., 2022. "Surrogate-Assisted Bounding-Box approach applied to constrained multi-objective optimisation under uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
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Keywords
Multi-objective optimization; Attainment function; Vorob’ev expectation; Expected Hypervolume Improvement; Kriging;
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