{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:48:37Z","timestamp":1760168917123,"version":"3.37.3"},"reference-count":28,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2019,1,8]],"date-time":"2019-01-08T00:00:00Z","timestamp":1546905600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Glob Optim"],"published-print":{"date-parts":[[2019,3]]},"DOI":"10.1007\/s10898-018-0716-0","type":"journal-article","created":{"date-parts":[[2019,1,9]],"date-time":"2019-01-09T00:09:02Z","timestamp":1546992542000},"page":"615-636","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Conditional optimization of a noisy function using a kriging metamodel"],"prefix":"10.1007","volume":"73","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9617-3923","authenticated-orcid":false,"given":"Diari\u00e9tou","family":"Sambakh\u00e9","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0478-3634","authenticated-orcid":false,"given":"Lauriane","family":"Rouan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jean-No\u00ebl","family":"Bacro","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9121-7835","authenticated-orcid":false,"given":"Eric","family":"Goz\u00e9","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,1,8]]},"reference":[{"key":"716_CR1","first-page":"231","volume-title":"Numerical methods of Nonlinear Optimization","author":"FH Branin","year":"1972","unstructured":"Branin, F.H., Hoo, S.K.: A method for finding multiple extrema of a function of n variables. In: Lootsma, F.A. (ed.) Numerical methods of Nonlinear Optimization, pp. 231\u2013237. Academic Press, London (1972)"},{"key":"716_CR2","volume-title":"Working with Dynamic Crop Models: Evaluation, Analysis, Parameterization, and Applications","author":"F Brun","year":"2006","unstructured":"Brun, F., Wallach, D., Makowski, D., Jones, J.W.: Working with Dynamic Crop Models: Evaluation, Analysis, Parameterization, and Applications. Elsevier, Amsterdam (2006)"},{"key":"716_CR3","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1016\/j.camwa.2004.12.014","volume":"50","author":"JM Calvin","year":"2005","unstructured":"Calvin, J.M., Zalinski, A.: One-dimensional global optimization for observations with noise. Comput. Math. Appl. 50, 157\u2013169 (2005)","journal-title":"Comput. Math. Appl."},{"key":"716_CR4","unstructured":"Carnell, R.: lhs: Latin Hypercube Samples. http:\/\/CRAN.R-project.org\/package=lhs , r package version 0.5, last access 15 (2011)"},{"key":"716_CR5","unstructured":"Cox, D.D., John, S.: SDO: a statistical method for global optimization. In: Alexandrov, N., Hussaini, M.Y. (eds.) Multidisciplinary Design Optimization: State of the Art, pp. 315\u2013329. SIAM, Philadelphia (1997)"},{"key":"716_CR6","doi-asserted-by":"crossref","DOI":"10.1002\/9781119115151","volume-title":"Statistics for Spatial Data","author":"N Cressie","year":"1993","unstructured":"Cressie, N.: Statistics for Spatial Data, Revised edn. Wiley, New York (1993)","edition":"Revised"},{"issue":"3","key":"716_CR7","doi-asserted-by":"publisher","first-page":"385","DOI":"10.1007\/BF00056241","volume":"17","author":"CM Donald","year":"1968","unstructured":"Donald, C.M.: The breeding of crop ideotypes. Euphytica 17(3), 385\u2013403 (1968)","journal-title":"Euphytica"},{"issue":"1","key":"716_CR8","doi-asserted-by":"publisher","first-page":"490","DOI":"10.1137\/130949555","volume":"2","author":"D Ginsbourger","year":"2014","unstructured":"Ginsbourger, D., Baccou, J., Chevalier, C., Perales, F., Garland, N., Monerie, Y.: Bayesian adaptive reconstruction of profile optima and optimizers. SIAM\/ASA J. Uncertain. Quantif. 2(1), 490\u2013510 (2014). https:\/\/doi.org\/10.1137\/130949555","journal-title":"SIAM\/ASA J. Uncertain. Quantif."},{"key":"716_CR9","unstructured":"Ginsbourger, D., Picheny, V., Roustant, O., Richet, Y.: A new look at kriging for the approximation of noisy simulators with tunable fidelity. 8th annual conference of ENBIS (2008)"},{"issue":"3","key":"716_CR10","doi-asserted-by":"publisher","first-page":"441","DOI":"10.1007\/s10898-005-2454-3","volume":"34","author":"D Huang","year":"2006","unstructured":"Huang, D., Allen, T.T., Notz, W.I., Zeng, N.: Global optimization of stochastic black-box systems via sequential kriging meta-models. J. Glob. Optim. 34(3), 441\u2013466 (2006)","journal-title":"J. Glob. Optim."},{"issue":"10","key":"716_CR11","doi-asserted-by":"publisher","first-page":"2331","DOI":"10.2514\/1.20068","volume":"44","author":"AIJ Forrester","year":"2006","unstructured":"Forrester, A.I.J., Keane, A.J., Bressloff, N.W.: Design and analysis of \u201cNoisy\u201d computer experiments. AIAA J. 44(10), 2331\u20132339 (2006). https:\/\/doi.org\/10.2514\/1.20068","journal-title":"AIAA J."},{"issue":"2","key":"716_CR12","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1016\/0378-3758(90)90122-B","volume":"26","author":"ME Johnson","year":"1990","unstructured":"Johnson, M.E., Moore, L.M., Ylvisaker, D.: Minimax and maximin distance designs. J. Stat. Plan. Inference 26(2), 131\u2013148 (1990)","journal-title":"J. Stat. Plan. Inference"},{"issue":"4","key":"716_CR13","doi-asserted-by":"publisher","first-page":"455","DOI":"10.1023\/A:1008306431147","volume":"13","author":"DR Jones","year":"1998","unstructured":"Jones, D.R., Schonlau, M., Welch, W.J.: Efficient global optimization of expensive black-box functions. J. Glob. Optim. 13(4), 455\u2013492 (1998). https:\/\/doi.org\/10.1023\/A:1008306431147","journal-title":"J. Glob. Optim."},{"key":"716_CR14","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.agsy.2012.08.002","volume":"114","author":"PG Jones","year":"2013","unstructured":"Jones, P.G., Thornton, P.K.: Generating downscaled weather data from a suite of climate models for agricultural modelling applications. Agric. Syst. 114, 1\u20135 (2013)","journal-title":"Agric. Syst."},{"key":"716_CR15","unstructured":"Krige, D.G.: A statistical approach to some mine valuation and allied problems on the Witwatersrand: By DG Krige. Ph.D. thesis, University of the Witwatersrand (1951)"},{"issue":"1","key":"716_CR16","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1115\/1.3653121","volume":"86","author":"HJ Kushner","year":"1964","unstructured":"Kushner, H.J.: A new method of locating the maximum point of an arbitrary multipeak curve in the presence of noise. J. Basic Eng. 86(1), 97 (1964). https:\/\/doi.org\/10.1115\/1.3653121","journal-title":"J. Basic Eng."},{"key":"716_CR17","unstructured":"Matheron, G.: Le krigeage universel. Les Cahiers du Centre de morphologie math\u00e9matique de Fontainebleau, vol. 1. \u00c9cole nationale sup\u00e9rieure des mines de Paris, Paris (1969)"},{"issue":"2","key":"716_CR18","doi-asserted-by":"publisher","first-page":"239","DOI":"10.1080\/00401706.1979.10489755","volume":"21","author":"MD McKay","year":"1979","unstructured":"McKay, M.D., Beckman, R.J., Conover, W.J.: Comparison of three methods for selecting values of input variables in the analysis of output from a computer code. Technometrics 21(2), 239\u2013245 (1979). https:\/\/doi.org\/10.1080\/00401706.1979.10489755","journal-title":"Technometrics"},{"key":"716_CR19","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611970081","volume-title":"Random number generation and Quasi-Monte Carlo methods","author":"H Niederreiter","year":"1992","unstructured":"Niederreiter, H.: Random number generation and Quasi-Monte Carlo methods. Society for Industrial and Applied Mathematics, Philadelphia (1992). https:\/\/doi.org\/10.1137\/1.9781611970081"},{"key":"716_CR20","doi-asserted-by":"publisher","first-page":"1035","DOI":"10.1016\/j.csda.2013.03.018","volume":"71","author":"V Picheny","year":"2014","unstructured":"Picheny, V., Ginsbourger, D.: Noisy kriging-based optimization methods: a unified implementation within the DiceOptim package. Comput. Stat. Data Anal. 71, 1035\u20131053 (2014). https:\/\/doi.org\/10.1016\/j.csda.2013.03.018","journal-title":"Comput. Stat. Data Anal."},{"issue":"1","key":"716_CR21","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1080\/00401706.2012.707580","volume":"55","author":"V Picheny","year":"2013","unstructured":"Picheny, V., Ginsbourger, D., Richet, Y., Caplin, G.: Quantile-based optimization of noisy computer experiments with tunable precision. Technometrics 55(1), 2\u201313 (2013). https:\/\/doi.org\/10.1080\/00401706.2012.707580","journal-title":"Technometrics"},{"issue":"3","key":"716_CR22","doi-asserted-by":"publisher","first-page":"607","DOI":"10.1007\/s00158-013-0919-4","volume":"48","author":"V Picheny","year":"2013","unstructured":"Picheny, V., Wagner, T., Ginsbourger, D.: A benchmark of kriging-based infill criteria for noisy optimization. Struct. Multidiscip. Optim. 48(3), 607\u2013626 (2013). https:\/\/doi.org\/10.1007\/s00158-013-0919-4","journal-title":"Struct. Multidiscip. Optim."},{"issue":"3","key":"716_CR23","doi-asserted-by":"publisher","first-page":"175","DOI":"10.1093\/comjnl\/3.3.175","volume":"3","author":"HH Rosenbrock","year":"1960","unstructured":"Rosenbrock, H.H.: An automatic method for finding the greatest or least value of a function. Comput. J. 3(3), 175\u2013184 (1960). https:\/\/doi.org\/10.1093\/comjnl\/3.3.175","journal-title":"Comput. J."},{"issue":"1","key":"716_CR24","doi-asserted-by":"publisher","first-page":"54","DOI":"10.18637\/jss.v051.i01","volume":"51","author":"O Roustant","year":"2012","unstructured":"Roustant, O., Ginsbourger, D., Deville, Y.: DiceKriging, DiceOptim: two R packages for the analysis of computer experiments by kriging-based metamodelling and optimization. J. Stat. Softw. 51(1), 54 (2012)","journal-title":"J. Stat. Softw."},{"key":"716_CR25","doi-asserted-by":"crossref","unstructured":"Sacks, J., Welch, W.J., Mitchell, T.J., Wynn, H.P.: Design and analysis of computer experiments. Stat. Sci. (1989)","DOI":"10.1214\/ss\/1177012420"},{"issue":"3","key":"716_CR26","doi-asserted-by":"publisher","first-page":"996","DOI":"10.1137\/100801275","volume":"21","author":"W Scott","year":"2011","unstructured":"Scott, W., Frazier, P., Powell, W.: The correlated knowledge gradient for simulation optimization of continuous parameters using gaussian process regression. SIAM J. Optim. 21(3), 996\u20131026 (2011). https:\/\/doi.org\/10.1137\/100801275","journal-title":"SIAM J. Optim."},{"issue":"11","key":"716_CR27","doi-asserted-by":"publisher","first-page":"3088","DOI":"10.1016\/j.jspi.2010.04.018","volume":"140","author":"E Vazquez","year":"2010","unstructured":"Vazquez, E., Bect, J.: Convergence properties of the expected improvement algorithm with fixed mean and covariance functions. J. Stat. Plan. Inference 140(11), 3088\u20133095 (2010). https:\/\/doi.org\/10.1016\/j.jspi.2010.04.018","journal-title":"J. Stat. Plan. Inference"},{"key":"716_CR28","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511813658","volume-title":"Probability with Martingales","author":"D Williams","year":"1991","unstructured":"Williams, D.: Probability with Martingales. Cambridge University Press, Cambridge (1991)"}],"container-title":["Journal of Global Optimization"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10898-018-0716-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10898-018-0716-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10898-018-0716-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,13]],"date-time":"2024-07-13T21:50:10Z","timestamp":1720907410000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10898-018-0716-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,1,8]]},"references-count":28,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2019,3]]}},"alternative-id":["716"],"URL":"https:\/\/doi.org\/10.1007\/s10898-018-0716-0","relation":{},"ISSN":["0925-5001","1573-2916"],"issn-type":[{"type":"print","value":"0925-5001"},{"type":"electronic","value":"1573-2916"}],"subject":[],"published":{"date-parts":[[2019,1,8]]},"assertion":[{"value":"1 November 2017","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 October 2018","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 January 2019","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}