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Efficient Global Optimization of Expensive Black-Box Functions

Jones, Donald R., Schonlau, Matthias, Welch, William J.·1998·Journal of Global Optimization

DOI 10.1023/a:1008306431147

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Authors: Jones, D. R., Schonlau, M., & Welch, W. J.
Affiliations: General Motors (United States) (US)
National Institute of Statistical Sciences (US)
University of Waterloo (CA)
ORCID: Jones, Donald R.
Schonlau, Matthias
Venue: Journal of Global Optimization
Publisher: Springer Science and Business Media LLC
Published: 1998-12
Volume: 13
Issue: 4
Pages: 455-492
ISSN: 0925-5001 (ISSN-L)
1573-2916
DOI: 10.1023/a:1008306431147
OpenAlex: W1510052597
Cited by: 8,070
References: 34
Citations by year: 2026: 730 · 2025: 661 · 2024: 601 · 2023: 599 · 2022: 636 · 2021: 659 · 2020: 612 · 2019: 548 · 2018: 458 · 2017: 369 · 2016: 370 · 2015: 284 · 2014: 255 · 2013: 219 · 2012: 215
FWCI: 7.84
Type: journal article
Language: en
Open access: closed
Licence: www.springernature.com/gp/researchers/text-and-data-mining (tdm)
www.springernature.com/gp/researchers/text-and-data-mining (vor)
Locations: Journal of Global Optimization (publishedVersion)
Topics: Physical Sciences › Mathematics › Numerical Analysis › Advanced Optimization Algorithms Research
Physical Sciences › Computer Science › Computational Theory and Mathematics › Advanced Multi-Objective Optimization Algorithms
Physical Sciences › Computer Science › Artificial Intelligence › Metaheuristic Optimization Algorithms Research
Keywords: expensive black-box functions, global optimization, response surface methodology, surrogate models, stopping rules, exploration-exploitation balance, prediction error, engineering design optimization

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Efficient Global Optimization of Expensive Black-Box Functions

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