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Parallel radial basis function methods for the global optimization of expensive functions

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Cited by:

  1. Fani Boukouvala & M. M. Faruque Hasan & Christodoulos A. Floudas, 2017. "Global optimization of general constrained grey-box models: new method and its application to constrained PDEs for pressure swing adsorption," Journal of Global Optimization, Springer, vol. 67(1), pages 3-42, January.
  2. Nadia Martinez & Hadis Anahideh & Jay M. Rosenberger & Diana Martinez & Victoria C. P. Chen & Bo Ping Wang, 2017. "Global optimization of non-convex piecewise linear regression splines," Journal of Global Optimization, Springer, vol. 68(3), pages 563-586, July.
  3. Juliane Müller, 2017. "SOCEMO: Surrogate Optimization of Computationally Expensive Multiobjective Problems," INFORMS Journal on Computing, INFORMS, vol. 29(4), pages 581-596, November.
  4. Juliane Müller & Jangho Park & Reetik Sahu & Charuleka Varadharajan & Bhavna Arora & Boris Faybishenko & Deborah Agarwal, 2021. "Surrogate optimization of deep neural networks for groundwater predictions," Journal of Global Optimization, Springer, vol. 81(1), pages 203-231, September.
  5. Komarudin & Tim De Feyter & Marie-Anne Guerry & Greet Vanden Berghe, 2020. "The extended roster quality staffing problem: addressing roster quality variation within a staffing planning period," Journal of Scheduling, Springer, vol. 23(2), pages 253-264, April.
  6. Hau T. Mai & Jaewook Lee & Joowon Kang & H. Nguyen-Xuan & Jaehong Lee, 2022. "An Improved Blind Kriging Surrogate Model for Design Optimization Problems," Mathematics, MDPI, vol. 10(16), pages 1-19, August.
  7. Zhe Zhou & Fusheng Bai, 2018. "An adaptive framework for costly black-box global optimization based on radial basis function interpolation," Journal of Global Optimization, Springer, vol. 70(4), pages 757-781, April.
  8. M. Joseane F. G. Macêdo & Elizabeth W. Karas & M. Fernanda P. Costa & Ana Maria A. C. Rocha, 2020. "Filter-based stochastic algorithm for global optimization," Journal of Global Optimization, Springer, vol. 77(4), pages 777-805, August.
  9. Chow, Joseph Y.J. & Regan, Amelia C., 2011. "Network-based real option models," Transportation Research Part B: Methodological, Elsevier, vol. 45(4), pages 682-695, May.
  10. Tipaluck Krityakierne & Taimoor Akhtar & Christine A. Shoemaker, 2016. "SOP: parallel surrogate global optimization with Pareto center selection for computationally expensive single objective problems," Journal of Global Optimization, Springer, vol. 66(3), pages 417-437, November.
  11. Liu, Haoxiang & Wang, David Z.W., 2017. "Locating multiple types of charging facilities for battery electric vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 103(C), pages 30-55.
  12. Wu, Xin & Zheng, Yi & Wu, Bin & Tian, Yong & Han, Feng & Zheng, Chunmiao, 2016. "Optimizing conjunctive use of surface water and groundwater for irrigation to address human-nature water conflicts: A surrogate modeling approach," Agricultural Water Management, Elsevier, vol. 163(C), pages 380-392.
  13. Juliane Müller & Joshua D. Woodbury, 2017. "GOSAC: global optimization with surrogate approximation of constraints," Journal of Global Optimization, Springer, vol. 69(1), pages 117-136, September.
  14. Andrea Cassioli & Fabio Schoen, 2013. "Global optimization of expensive black box problems with a known lower bound," Journal of Global Optimization, Springer, vol. 57(1), pages 177-190, September.
  15. Taimoor Akhtar & Christine Shoemaker, 2016. "Multi objective optimization of computationally expensive multi-modal functions with RBF surrogates and multi-rule selection," Journal of Global Optimization, Springer, vol. 64(1), pages 17-32, January.
  16. Rommel Regis & Christine Shoemaker, 2013. "A quasi-multistart framework for global optimization of expensive functions using response surface models," Journal of Global Optimization, Springer, vol. 56(4), pages 1719-1753, August.
  17. Richard T. Lyons & Richard C. Peralta & Partha Majumder, 2020. "Comparing Single-Objective Optimization Protocols for Calibrating the Birds Nest Aquifer Model—A Problem Having Multiple Local Optima," IJERPH, MDPI, vol. 17(3), pages 1-10, January.
  18. Wenyu Wang & Christine A. Shoemaker, 2023. "Reference Vector Assisted Candidate Search with Aggregated Surrogate for Computationally Expensive Many Objective Optimization Problems," INFORMS Journal on Computing, INFORMS, vol. 35(2), pages 318-334, March.
  19. Dawei Zhan & Jiachang Qian & Yuansheng Cheng, 2017. "Pseudo expected improvement criterion for parallel EGO algorithm," Journal of Global Optimization, Springer, vol. 68(3), pages 641-662, July.
  20. Belmiro P. M. Duarte & Anthony C. Atkinson & Satya P. Singh & Marco S. Reis, 2023. "Optimal design of experiments for hypothesis testing on ordered treatments via intersection-union tests," Statistical Papers, Springer, vol. 64(2), pages 587-615, April.
  21. M Laguna & J Molina & F Pérez & R Caballero & A G Hernández-Díaz, 2010. "The challenge of optimizing expensive black boxes: a scatter search/rough set theory approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(1), pages 53-67, January.
  22. Charles Audet & Edward Hallé-Hannan & Sébastien Le Digabel, 2023. "A General Mathematical Framework for Constrained Mixed-variable Blackbox Optimization Problems with Meta and Categorical Variables," SN Operations Research Forum, Springer, vol. 4(1), pages 1-37, March.
  23. Juliane Müller & Marcus Day, 2019. "Surrogate Optimization of Computationally Expensive Black-Box Problems with Hidden Constraints," INFORMS Journal on Computing, INFORMS, vol. 31(4), pages 689-702, October.
  24. Juliane Müller & Christine Shoemaker & Robert Piché, 2014. "SO-I: a surrogate model algorithm for expensive nonlinear integer programming problems including global optimization applications," Journal of Global Optimization, Springer, vol. 59(4), pages 865-889, August.
  25. Juliane Müller & Christine Shoemaker, 2014. "Influence of ensemble surrogate models and sampling strategy on the solution quality of algorithms for computationally expensive black-box global optimization problems," Journal of Global Optimization, Springer, vol. 60(2), pages 123-144, October.
  26. Chen, Mingjie & Tompson, Andrew F.B. & Mellors, Robert J. & Ramirez, Abelardo L. & Dyer, Kathleen M. & Yang, Xianjin & Wagoner, Jeffrey L., 2014. "An efficient Bayesian inversion of a geothermal prospect using a multivariate adaptive regression spline method," Applied Energy, Elsevier, vol. 136(C), pages 619-627.
  27. Chen, Mingjie & Tompson, Andrew F.B. & Mellors, Robert J. & Abdalla, Osman, 2015. "An efficient optimization of well placement and control for a geothermal prospect under geological uncertainty," Applied Energy, Elsevier, vol. 137(C), pages 352-363.
  28. Liu, Haoxiang & Szeto, W.Y. & Long, Jiancheng, 2019. "Bike network design problem with a path-size logit-based equilibrium constraint: Formulation, global optimization, and matheuristic," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 127(C), pages 284-307.
  29. Tian, Qingyun & Wang, David Z.W. & Lin, Yun Hui, 2022. "Optimal deployment of autonomous buses into a transit service network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 165(C).
  30. Boukouvala, Fani & Misener, Ruth & Floudas, Christodoulos A., 2016. "Global optimization advances in Mixed-Integer Nonlinear Programming, MINLP, and Constrained Derivative-Free Optimization, CDFO," European Journal of Operational Research, Elsevier, vol. 252(3), pages 701-727.
  31. Krityakierne, Tipaluck & Baowan, Duangkamon, 2020. "Aggregated GP-based Optimization for Contaminant Source Localization," Operations Research Perspectives, Elsevier, vol. 7(C).
  32. Ray-Bing Chen & Yuan Wang & C. F. Jeff Wu, 2020. "Finding optimal points for expensive functions using adaptive RBF-based surrogate model via uncertainty quantification," Journal of Global Optimization, Springer, vol. 77(4), pages 919-948, August.
  33. Siem, A.Y.D. & den Hertog, D., 2007. "Kriging Models That Are Robust With Respect to Simulation Errors," Other publications TiSEM fe73dc8b-20d6-4f50-95eb-f, Tilburg University, School of Economics and Management.
  34. Logan Mathesen & Giulia Pedrielli & Szu Hui Ng & Zelda B. Zabinsky, 2021. "Stochastic optimization with adaptive restart: a framework for integrated local and global learning," Journal of Global Optimization, Springer, vol. 79(1), pages 87-110, January.
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