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Constrained Global Optimization of Expensive Black Box Functions Using Radial Basis Functions

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Cited by:

  1. Zheng, Liang & Xue, Xinfeng & Xu, Chengcheng & Ran, Bin, 2019. "A stochastic simulation-based optimization method for equitable and efficient network-wide signal timing under uncertainties," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 287-308.
  2. Driessen, L. & Brekelmans, R.C.M. & Gerichhausen, M. & Hamers, H.J.M. & den Hertog, D., 2006. "Why Methods for Optimization Problems with Time-Consuming Function Evaluations and Integer Variables Should Use Global Approximation Models," Other publications TiSEM 45a73d28-9fed-4b4c-a909-1, Tilburg University, School of Economics and Management.
  3. 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.
  4. H. Le Thi & A. Vaz & L. Vicente, 2012. "Optimizing radial basis functions by d.c. programming and its use in direct search for global derivative-free optimization," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 20(1), pages 190-214, April.
  5. Saleem Ramadan, 2016. "A Hybrid Global Optimization Method Based on Genetic Algorithm and Shrinking Box," Modern Applied Science, Canadian Center of Science and Education, vol. 10(2), pages 1-67, February.
  6. Vasileios Christelis & Aristotelis Mantoglou, 2016. "Coastal Aquifer Management Based on the Joint use of Density-Dependent and Sharp Interface Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(2), pages 861-876, January.
  7. Fusheng Bai & Dongchi Zou & Yutao Wei, 2024. "A surrogate-assisted evolutionary algorithm with clustering-based sampling for high-dimensional expensive blackbox optimization," Journal of Global Optimization, Springer, vol. 89(1), pages 93-115, May.
  8. Alberto Bemporad, 2020. "Global optimization via inverse distance weighting and radial basis functions," Computational Optimization and Applications, Springer, vol. 77(2), pages 571-595, November.
  9. 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.
  10. Vasileios Christelis & Aristotelis Mantoglou, 2016. "Pumping Optimization of Coastal Aquifers Assisted by Adaptive Metamodelling Methods and Radial Basis Functions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(15), pages 5845-5859, December.
  11. C. J. Price & M. Reale & B. L. Robertson, 2016. "Stochastic filter methods for generally constrained global optimization," Journal of Global Optimization, Springer, vol. 65(3), pages 441-456, July.
  12. Platt, Donovan, 2020. "A comparison of economic agent-based model calibration methods," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
  13. Hoseinzade, Davood & Lakzian, Esmail & Hashemian, Ali, 2021. "A blackbox optimization of volumetric heating rate for reducing the wetness of the steam flow through turbine blades," Energy, Elsevier, vol. 220(C).
  14. Dawei Zhan & Huanlai Xing, 2020. "Expected improvement for expensive optimization: a review," Journal of Global Optimization, Springer, vol. 78(3), pages 507-544, November.
  15. Liang Zheng & Ji Bao & Zhen Tan, 2025. "Robust simulation-based optimization for multiobjective problems with constraints," Annals of Operations Research, Springer, vol. 346(2), pages 1897-1927, March.
  16. Mahmood Mahmoodian & Juan Pablo Carbajal & Vasilis Bellos & Ulrich Leopold & Georges Schutz & Francois Clemens, 2018. "A Hybrid Surrogate Modelling Strategy for Simplification of Detailed Urban Drainage Simulators," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(15), pages 5241-5256, December.
  17. 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.
  18. 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.
  19. Juliane Müller & Robert Piché, 2011. "Mixture surrogate models based on Dempster-Shafer theory for global optimization problems," Journal of Global Optimization, Springer, vol. 51(1), pages 79-104, September.
  20. Rommel G. Regis & Christine A. Shoemaker, 2009. "Parallel Stochastic Global Optimization Using Radial Basis Functions," INFORMS Journal on Computing, INFORMS, vol. 21(3), pages 411-426, August.
  21. Yaohui Li & Yizhong Wu & Jianjun Zhao & Liping Chen, 2017. "A Kriging-based constrained global optimization algorithm for expensive black-box functions with infeasible initial points," Journal of Global Optimization, Springer, vol. 67(1), pages 343-366, January.
  22. C. J. Price & M. Reale & B. L. Robertson, 2021. "Oscars-ii: an algorithm for bound constrained global optimization," Journal of Global Optimization, Springer, vol. 79(1), pages 39-57, January.
  23. Charles Audet & Sébastien Le Digabel & Renaud Saltet, 2022. "Quantifying uncertainty with ensembles of surrogates for blackbox optimization," Computational Optimization and Applications, Springer, vol. 83(1), pages 29-66, September.
  24. Stinstra, E., 2006. "The meta-model approach for simulation-based design optimization," Other publications TiSEM 713f828a-4716-4a19-af00-e, Tilburg University, School of Economics and Management.
  25. 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.
  26. Regis, Rommel G. & Shoemaker, Christine A., 2007. "Parallel radial basis function methods for the global optimization of expensive functions," European Journal of Operational Research, Elsevier, vol. 182(2), pages 514-535, October.
  27. 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.
  28. Donovan Platt, 2019. "A Comparison of Economic Agent-Based Model Calibration Methods," Papers 1902.05938, arXiv.org.
  29. 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.
  30. Zan Yang & Haobo Qiu & Liang Gao & Chen Jiang & Jinhao Zhang, 2019. "Two-layer adaptive surrogate-assisted evolutionary algorithm for high-dimensional computationally expensive problems," Journal of Global Optimization, Springer, vol. 74(2), pages 327-359, June.
  31. Lehmann, Sebastian & Huth, Andreas, 2015. "Fast calibration of a dynamic vegetation model with minimum observation data," Ecological Modelling, Elsevier, vol. 301(C), pages 98-105.
  32. Konstantin Barkalov & Ilya Lebedev & Marina Usova & Daria Romanova & Daniil Ryazanov & Sergei Strijhak, 2022. "Optimization of Turbulence Model Parameters Using the Global Search Method Combined with Machine Learning," Mathematics, MDPI, vol. 10(15), pages 1-20, July.
  33. 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.
  34. 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.
  35. Krityakierne, Tipaluck & Baowan, Duangkamon, 2020. "Aggregated GP-based Optimization for Contaminant Source Localization," Operations Research Perspectives, Elsevier, vol. 7(C).
  36. Williams, Brian J. & Loeppky, Jason L. & Moore, Leslie M. & Macklem, Mason S., 2011. "Batch sequential design to achieve predictive maturity with calibrated computer models," Reliability Engineering and System Safety, Elsevier, vol. 96(9), pages 1208-1219.
  37. Davide Previtali & Mirko Mazzoleni & Antonio Ferramosca & Fabio Previdi, 2023. "GLISp-r: a preference-based optimization algorithm with convergence guarantees," Computational Optimization and Applications, Springer, vol. 86(1), pages 383-420, September.
  38. Luis Rios & Nikolaos Sahinidis, 2013. "Derivative-free optimization: a review of algorithms and comparison of software implementations," Journal of Global Optimization, Springer, vol. 56(3), pages 1247-1293, July.
  39. Aristotelis Charalampakis, 2012. "Registrar: a complete-memory operator to enhance performance of genetic algorithms," Journal of Global Optimization, Springer, vol. 54(3), pages 449-483, November.
  40. Vasileios Christelis & Aristotelis Mantoglou, 2016. "Coastal Aquifer Management Based on the Joint use of Density-Dependent and Sharp Interface Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(2), pages 861-876, January.
  41. Jesús Martínez-Frutos & David Herrero-Pérez, 2016. "Kriging-based infill sampling criterion for constraint handling in multi-objective optimization," Journal of Global Optimization, Springer, vol. 64(1), pages 97-115, January.
  42. Haitao Liu & Shengli Xu & Ying Ma & Xiaofang Wang, 2015. "Global optimization of expensive black box functions using potential Lipschitz constants and response surfaces," Journal of Global Optimization, Springer, vol. 63(2), pages 229-251, October.
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