The DOI matches its Crossref record; 25 of the 25 references it cites were found in a registry or an index.
A rigorous framework for optimization of expensive functions by surrogates
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Citations
Cites
McKay, M. D., Beckman, R. J., & Conover, W. J. (2000) · Technometrics · doi:10.2307/1271432 · Cited by 7,415
Design and Analysis of Computer Experiments
Sacks, J., Welch, W. J., Mitchell, T. J., & Wynn, H. P. (1989) · Statistical Science · doi:10.1214/ss/1177012413 · Cited by 6,919
Large Sample Properties of Simulations Using Latin Hypercube Sampling
Stein, M. (1987) · Technometrics · doi:10.1080/00401706.1987.10488205 · Cited by 2,471
Snir, M., Otto, S. W., WALKER, D. W., Dongarra, J. J., & Huss‐Lederman, S. (1996) · Cited by 2,152
The Jackknife Estimate of Variance
Efron, B., & Stein, C. (1981) · The Annals of Statistics · doi:10.1214/aos/1176345462 · Cited by 1,436
On the Convergence of Pattern Search Algorithms
Torczon, V. (1997) · SIAM Journal on Optimization · doi:10.1137/s1052623493250780 · Cited by 1,336
Self-citationA Predictive Approach to Model Selection
Geisser, S., & Eddy, W. F. (1979) · Journal of the American Statistical Association · doi:10.1080/01621459.1979.10481632 · Cited by 988
Orthogonal Array-Based Latin Hypercubes
Tang, B. (1993) · Journal of the American Statistical Association · doi:10.1080/01621459.1993.10476423 · Cited by 858
Zimmermann, H. (1979) · European Journal of Operational Research · doi:10.1016/0377-2217(79)90240-6 · Cited by 698
Statistical Inference for Spatial Processes
Ripley, B. D. (1988) · doi:10.1017/cbo9780511624131 · Cited by 546
Cited by
Accessorize to a Crime: Real and Stealthy Attacks on State-of-the-Art Face Recognition
Sharif, M., Bhagavatula, S., Bauer, L., & Reiter, M. K. (2016) · Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security · doi:10.1145/2976749.2978392 · Cited by 1,530
Derivative-free optimization: a review of algorithms and comparison of software implementations
Rios, L. M., & Sahinidis, N. V. (2013) · Journal of Global Optimization · doi:10.1007/s10898-012-9951-y · Cited by 1,276
Mesh Adaptive Direct Search Algorithms for Constrained Optimization
Audet, C., & Dennis, J. E. (2006) · SIAM Journal on Optimization · doi:10.1137/040603371 · Cited by 1,243
Self-citationUse of Kriging Models to Approximate Deterministic Computer Models
Martin, J. D., & Simpson, T. W. (2005) · AIAA Journal · doi:10.2514/1.8650 · Cited by 835
Biegler, L. T., & Grossmann, I. E. (2004) · Computers & Chemical Engineering · doi:10.1016/j.compchemeng.2003.11.003 · Cited by 593
Metadata
- Authors
- Booker, A. J., Dennis, J. E., Frank, P. D., Serafini, D. B., Torczon, V., & Trosset, M. W.
- Venue
- Structural Optimization
- Published
- 1999-02
- Volume
- 17
- Issue
- 1
- Pages
- 1-13
- ISSN
- 1615-147X (ISSN-L)
- 0934-4373
- 1615-1488
- OpenAlex
- W1985412770
- Cited by
- 960
- References
- 25
- FWCI
- 24.29
- Type
- journal article
- Language
- en
- Open access
- closed
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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How to cite
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- CoChat. (2026). Citation check: A rigorous framework for optimization of expensive functions by surrogates. https://app.cochat.ai/papers/10.1007/bf01197708
- The paper
- Booker, A. J., Dennis, J. E., Frank, P. D., Serafini, D. B., Torczon, V., & Trosset, M. W. (1999). A rigorous framework for optimization of expensive functions by surrogates. Structural Optimization. https://doi.org/10.1007/bf01197708
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
