{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,17]],"date-time":"2025-12-17T07:07:36Z","timestamp":1765955256793,"version":"3.48.0"},"reference-count":74,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Glob Optim"],"published-print":{"date-parts":[[2025,12]]},"DOI":"10.1007\/s10898-025-01566-6","type":"journal-article","created":{"date-parts":[[2025,12,2]],"date-time":"2025-12-02T07:35:35Z","timestamp":1764660935000},"page":"989-1026","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A surrogate-based adaptive sampling approach for mixed-integer black-box optimization problems"],"prefix":"10.1007","volume":"93","author":[{"given":"Emmanouil","family":"Karantoumanis","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5876-9945","authenticated-orcid":false,"given":"Nikolaos","family":"Ploskas","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,12,2]]},"reference":[{"key":"1566_CR1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-68913-5","volume-title":"Derivative-free and Blackbox Optimization","author":"C Audet","year":"2017","unstructured":"Audet, C., Hare, W.: Derivative-free and Blackbox Optimization. Springer, Cham (2017)"},{"issue":"1","key":"1566_CR2","first-page":"1","volume":"97","author":"T B\u00e4ck","year":"1997","unstructured":"B\u00e4ck, T., Fogel, D.B., Michalewicz, Z.: Handbook of evolutionary computation. Release 97(1), 1 (1997)","journal-title":"Release"},{"issue":"2","key":"1566_CR3","doi-asserted-by":"publisher","first-page":"490","DOI":"10.1109\/TEVC.2024.3496193","volume":"29","author":"MW Przewozniczek","year":"2024","unstructured":"Przewozniczek, M.W., Frej, B., Komarnicki, M.M.: From direct to directional variable dependencies-non-symmetrical dependencies discovery in real-world and theoretical problems. IEEE Trans. Evol. Comput. 29(2), 490\u2013504 (2024)","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"1","key":"1566_CR4","doi-asserted-by":"publisher","first-page":"148","DOI":"10.1109\/JPROC.2015.2494218","volume":"104","author":"B Shahriari","year":"2015","unstructured":"Shahriari, B., Swersky, K., Wang, Z., Adams, R.P., De Freitas, N.: Taking the human out of the loop: a review of bayesian optimization. Proc. IEEE 104(1), 148\u2013175 (2015)","journal-title":"Proc. IEEE"},{"key":"1566_CR5","doi-asserted-by":"crossref","unstructured":"Conn, A.R., Scheinberg, K., Vicente, L.N.: Introduction to Derivative-Free Optimization. Society for Industrial and Applied Mathematics, USA (2009)","DOI":"10.1137\/1.9780898718768"},{"key":"1566_CR6","doi-asserted-by":"publisher","first-page":"287","DOI":"10.1017\/S0962492919000060","volume":"28","author":"J Larson","year":"2019","unstructured":"Larson, J., Menickelly, M., Wild, S.M.: Derivative-free optimization methods. Acta Numer. 28, 287\u2013404 (2019)","journal-title":"Acta Numer."},{"issue":"4","key":"1566_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1916461.1916468","volume":"37","author":"S Le Digabel","year":"2011","unstructured":"Le Digabel, S.: Algorithm 909: NOMAD: nonlinear optimization with the MADS algorithm. ACM Trans. Math. Softw. (TOMS) 37(4), 1\u201315 (2011)","journal-title":"ACM Trans. Math. Softw. (TOMS)"},{"issue":"3","key":"1566_CR8","doi-asserted-by":"publisher","first-page":"385","DOI":"10.1137\/S003614450242889","volume":"45","author":"TG Kolda","year":"2003","unstructured":"Kolda, T.G., Lewis, R.M., Torczon, V.: Optimization by direct search: new perspectives on some classical and modern methods. SIAM Rev. 45(3), 385\u2013482 (2003)","journal-title":"SIAM Rev."},{"key":"1566_CR9","doi-asserted-by":"publisher","unstructured":"Powell, M.J.D.: In: Gomez, S., Hennart, J.-P. (eds.) A Direct Search Optimization Method That Models the Objective and Constraint Functions by Linear Interpolation, pp. 51\u201367. Springer, Dordrecht (1994). https:\/\/doi.org\/10.1007\/978-94-015-8330-5_4","DOI":"10.1007\/978-94-015-8330-5_4"},{"key":"1566_CR10","unstructured":"Powell, M.J., et al.: The BOBYQA algorithm for bound constrained optimization without derivatives. Cambridge NA Report NA2009\/06, University of Cambridge, Cambridge 26, 26\u201346 (2009)"},{"key":"1566_CR11","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. Global Optim. 13, 455\u2013492 (1998)","journal-title":"J. Global Optim."},{"issue":"4","key":"1566_CR12","doi-asserted-by":"publisher","first-page":"525","DOI":"10.1007\/s00224-004-1177-z","volume":"39","author":"S Droste","year":"2006","unstructured":"Droste, S., Jansen, T., Wegener, I.: Upper and lower bounds for randomized search heuristics in black-box optimization. Theory Comput. Syst. 39(4), 525\u2013544 (2006)","journal-title":"Theory Comput. Syst."},{"key":"1566_CR13","doi-asserted-by":"crossref","unstructured":"Doerr, C.: Complexity theory for discrete black-box optimization heuristics. Theory Evol. Comput.: Recent Dev. Discrete Optim. 133\u2013212 (2020)","DOI":"10.1007\/978-3-030-29414-4_3"},{"issue":"2","key":"1566_CR14","doi-asserted-by":"publisher","first-page":"387","DOI":"10.1007\/s00500-016-2474-6","volume":"22","author":"D Wang","year":"2018","unstructured":"Wang, D., Tan, D., Liu, L.: Particle swarm optimization algorithm: an overview. Soft. Comput. 22(2), 387\u2013408 (2018)","journal-title":"Soft. Comput."},{"key":"1566_CR15","doi-asserted-by":"crossref","unstructured":"Kennedy, J., Eberhart, R.: Particle swarm optimization. In: Proceedings of ICNN\u201995-international Conference on Neural Networks, vol. 4, pp. 1942\u20131948 (1995). ieee","DOI":"10.1109\/ICNN.1995.488968"},{"issue":"2","key":"1566_CR16","doi-asserted-by":"publisher","first-page":"265","DOI":"10.1007\/s10589-009-9283-0","volume":"46","author":"AL Cust\u00f3dio","year":"2010","unstructured":"Cust\u00f3dio, A.L., Rocha, H., Vicente, L.N.: Incorporating minimum frobenius norm models in direct search. Comput. Optim. Appl. 46(2), 265\u2013278 (2010)","journal-title":"Comput. Optim. Appl."},{"issue":"6","key":"1566_CR17","doi-asserted-by":"publisher","first-page":"1433","DOI":"10.1007\/s11590-019-01452-7","volume":"13","author":"C Audet","year":"2019","unstructured":"Audet, C., C\u00f4t\u00e9-Massicotte, J.: Dynamic improvements of static surrogates in direct search optimization. Optim. Lett. 13(6), 1433\u20131447 (2019)","journal-title":"Optim. Lett."},{"key":"1566_CR18","doi-asserted-by":"publisher","first-page":"250","DOI":"10.1016\/j.compchemeng.2017.09.017","volume":"108","author":"A Bhosekar","year":"2018","unstructured":"Bhosekar, A., Ierapetritou, M.: Advances in surrogate based modeling, feasibility analysis, and optimization: A review. Comput. Chem. Eng. 108, 250\u2013267 (2018)","journal-title":"Comput. Chem. Eng."},{"key":"1566_CR19","doi-asserted-by":"publisher","DOI":"10.1016\/j.apenergy.2022.118537","volume":"310","author":"LF Santos","year":"2022","unstructured":"Santos, L.F., Costa, C.B., Caballero, J.A., Ravagnani, M.A.: Framework for embedding black-box simulation into mathematical programming via kriging surrogate model applied to natural gas liquefaction process optimization. Appl. Energy 310, 118537 (2022)","journal-title":"Appl. Energy"},{"issue":"4","key":"1566_CR20","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s11081-023-09879-9","volume":"25","author":"DJ Papageorgiou","year":"2024","unstructured":"Papageorgiou, D.J., Kronqvist, J., Kumaran, K.: Linewalker: line search for black box derivative-free optimization and surrogate model construction. Optim. Eng. 25(4), 1\u201365 (2024)","journal-title":"Optim. Eng."},{"issue":"3","key":"1566_CR21","doi-asserted-by":"publisher","first-page":"1463","DOI":"10.1007\/s11081-022-09740-5","volume":"24","author":"J Zhai","year":"2023","unstructured":"Zhai, J., Boukouvala, F.: Surrogate-based branch-and-bound algorithms for simulation-based black-box optimization. Optim. Eng. 24(3), 1463\u20131491 (2023)","journal-title":"Optim. Eng."},{"key":"1566_CR22","doi-asserted-by":"publisher","first-page":"865","DOI":"10.1007\/s10898-013-0101-y","volume":"59","author":"J M\u00fcller","year":"2014","unstructured":"M\u00fcller, J., Shoemaker, C.A., Pich\u00e9, R.: SO-I: a surrogate model algorithm for expensive nonlinear integer programming problems including global optimization applications. J. Global Optim. 59, 865\u2013889 (2014)","journal-title":"J. Global Optim."},{"key":"1566_CR23","unstructured":"Dubreuil, S., Bartoli, N., Berthelin, G., Vila, O.C., Gogu, C., Lefebvre, T., Morlier, J., Sala\u00fcn, M.: Development of MDO formulations based on disciplinary surrogate models by gaussian processes. In: AeroBest (2021)"},{"issue":"9","key":"1566_CR24","doi-asserted-by":"publisher","first-page":"3537","DOI":"10.5194\/gmd-15-3537-2022","volume":"15","author":"S Oliver","year":"2022","unstructured":"Oliver, S., Cartis, C., Kriest, I., Tett, S.F.B., Khatiwala, S.: A derivative-free optimisation method for global ocean biogeochemical models. Geoscientific Model Development 15(9), 3537\u20133554 (2022)","journal-title":"Geoscientific Model Development"},{"key":"1566_CR25","doi-asserted-by":"publisher","first-page":"895","DOI":"10.1007\/s11590-016-1028-2","volume":"11","author":"F Boukouvala","year":"2017","unstructured":"Boukouvala, F., Floudas, C.A.: ARGONAUT: algorithms for global optimization of constrained grey-box computational problems. Optim. Lett. 11, 895\u2013913 (2017)","journal-title":"Optim. Lett."},{"key":"1566_CR26","doi-asserted-by":"publisher","first-page":"177","DOI":"10.1007\/s11081-015-9281-2","volume":"17","author":"J M\u00fcller","year":"2016","unstructured":"M\u00fcller, J.: MISO: mixed-integer surrogate optimization framework. Optim. Eng. 17, 177\u2013203 (2016)","journal-title":"Optim. Eng."},{"key":"1566_CR27","first-page":"70","volume":"2017","author":"A-S Cr\u00e9lot","year":"2017","unstructured":"Cr\u00e9lot, A.-S., Beauthier, C., Orban, D., Sainvitu, C., Sartenaer, A.: Combining surrogate strategies with MADS for mixed-variable derivative-free optimization. Cahier du GERAD G 2017, 70 (2017)","journal-title":"Cahier du GERAD G"},{"key":"1566_CR28","doi-asserted-by":"publisher","first-page":"457","DOI":"10.1016\/j.ins.2022.11.045","volume":"619","author":"J K\u00fadela","year":"2023","unstructured":"K\u00fadela, J., Matou\u0161ek, R.: Combining lipschitz and RBF surrogate models for high-dimensional computationally expensive problems. Inf. Sci. 619, 457\u2013477 (2023)","journal-title":"Inf. Sci."},{"issue":"4","key":"1566_CR29","doi-asserted-by":"publisher","first-page":"644","DOI":"10.1109\/TEVC.2017.2675628","volume":"21","author":"C Sun","year":"2017","unstructured":"Sun, C., Jin, Y., Cheng, R., Ding, J., Zeng, J.: Surrogate-assisted cooperative swarm optimization of high-dimensional expensive problems. IEEE Trans. Evol. Comput. 21(4), 644\u2013660 (2017)","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"4","key":"1566_CR30","doi-asserted-by":"publisher","first-page":"402","DOI":"10.1007\/s41019-022-00193-5","volume":"7","author":"CKJ Hou","year":"2022","unstructured":"Hou, C.K.J., Behdinan, K.: Dimensionality reduction in surrogate modeling: a review of combined methods. Data Sci. Eng. 7(4), 402\u2013427 (2022)","journal-title":"Data Sci. Eng."},{"issue":"6","key":"1566_CR31","doi-asserted-by":"publisher","first-page":"2211","DOI":"10.1002\/aic.14418","volume":"60","author":"A Cozad","year":"2014","unstructured":"Cozad, A., Sahinidis, N.V., Miller, D.C.: Learning surrogate models for simulation-based optimization. AIChE J. 60(6), 2211\u20132227 (2014)","journal-title":"AIChE J."},{"issue":"2","key":"1566_CR32","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1377612.1377613","volume":"35","author":"W Huyer","year":"2008","unstructured":"Huyer, W., Neumaier, A.: SNOBFIT-stable noisy optimization by branch and fit. ACM Trans. Math. Softw. (TOMS) 35(2), 1\u201325 (2008)","journal-title":"ACM Trans. Math. Softw. (TOMS)"},{"key":"1566_CR33","unstructured":"MINLPLib: A library of mixed-integer and continuous nonlinear programming instances. https:\/\/www.minlplib.org\/index.html (2023)"},{"key":"1566_CR34","unstructured":"Tomofumi Yuki, L.-N.P.: PolyBenchC-4.2.1. https:\/\/github.com\/MatthiasJReisinger\/PolyBenchC-4.2.1. last accessed on June 30, 2024 (2016)"},{"key":"1566_CR35","doi-asserted-by":"publisher","first-page":"1247","DOI":"10.1007\/s10898-012-9951-y","volume":"56","author":"LM Rios","year":"2013","unstructured":"Rios, L.M., Sahinidis, N.V.: Derivative-free optimization: a review of algorithms and comparison of software implementations. J. Global Optim. 56, 1247\u20131293 (2013)","journal-title":"J. Global Optim."},{"key":"1566_CR36","doi-asserted-by":"publisher","first-page":"433","DOI":"10.1007\/s10898-021-01085-0","volume":"82","author":"N Ploskas","year":"2022","unstructured":"Ploskas, N., Sahinidis, N.V.: Review and comparison of algorithms and software for mixed-integer derivative-free optimization. J. Global Optim. 82, 433\u2013462 (2022)","journal-title":"J. Global Optim."},{"key":"1566_CR37","unstructured":"Ingber, L., et al.: Adaptive simulated annealing (ASA). Global optimization C-code, Caltech Alumni Association, Pasadena, CA (1993)"},{"key":"1566_CR38","doi-asserted-by":"crossref","unstructured":"Adams, B.M., Bohnhoff, W.J., Dalbey, K.R., Ebeida, M.S., Eddy, J.P., Eldred, M.S., Hooper, R.W., Hough, P.D., Hu, K.T., Jakeman, J.D., et al.: Dakota, a multilevel parallel object-oriented framework for design optimization, parameter estimation, uncertainty quantification, and sensitivity analysis: version 6.13 user\u2019s manual. Technical report, Sandia National Lab.(SNL-NM), Albuquerque, NM (United States) (2020)","DOI":"10.2172\/1817318"},{"key":"1566_CR39","unstructured":"Hansen, N.: The CMA evolution strategy: A tutorial. arXiv preprint arXiv:1604.00772 (2016)"},{"issue":"4\u20135","key":"1566_CR40","doi-asserted-by":"publisher","first-page":"669","DOI":"10.1080\/10556780902909948","volume":"24","author":"AIF Vaz","year":"2009","unstructured":"Vaz, A.I.F., Vicente, L.N.: PSwarm: a hybrid solver for linearly constrained global derivative-free optimization. Optim. Methods Softw. 24(4\u20135), 669\u2013685 (2009)","journal-title":"Optim. Methods Softw."},{"key":"1566_CR41","doi-asserted-by":"publisher","first-page":"597","DOI":"10.1007\/s12532-018-0144-7","volume":"10","author":"A Costa","year":"2018","unstructured":"Costa, A., Nannicini, G.: RBFOpt: an open-source library for black-box optimization with costly function evaluations. Math. Program. Comput. 10, 597\u2013629 (2018)","journal-title":"Math. Program. Comput."},{"key":"1566_CR42","unstructured":"Audet, C., Digabel, S.L., Montplaisir, V.R., Tribes, C.: NOMAD version 4: Nonlinear optimization with the MADS algorithm. arXiv preprint arXiv:2104.11627 (2021)"},{"issue":"3","key":"1566_CR43","doi-asserted-by":"publisher","first-page":"642","DOI":"10.1137\/040620886","volume":"17","author":"C Audet","year":"2006","unstructured":"Audet, C., Orban, D.: Finding optimal algorithmic parameters using derivative-free optimization. SIAM J. Optim. 17(3), 642\u2013664 (2006)","journal-title":"SIAM J. Optim."},{"key":"1566_CR44","doi-asserted-by":"publisher","DOI":"10.1145\/3085592","author":"M Porcelli","year":"2017","unstructured":"Porcelli, M., Toint, P.L.: BFO, a trainable derivative-free brute force optimizer for nonlinear bound-constrained optimization and equilibrium computations with continuous and discrete variables. ACM Trans. Math. Softw. (2017). https:\/\/doi.org\/10.1145\/3085592","journal-title":"ACM Trans. Math. Softw."},{"key":"1566_CR45","doi-asserted-by":"publisher","first-page":"505","DOI":"10.1007\/s10589-011-9405-3","volume":"53","author":"G Liuzzi","year":"2012","unstructured":"Liuzzi, G., Lucidi, S., Rinaldi, F.: Derivative-free methods for bound constrained mixed-integer optimization. Comput. Optim. Appl. 53, 505\u2013526 (2012)","journal-title":"Comput. Optim. Appl."},{"key":"1566_CR46","doi-asserted-by":"publisher","first-page":"933","DOI":"10.1007\/s10957-014-0617-4","volume":"164","author":"G Liuzzi","year":"2015","unstructured":"Liuzzi, G., Lucidi, S., Rinaldi, F.: Derivative-free methods for mixed-integer constrained optimization problems. J. Optim. Theory Appl. 164, 933\u2013965 (2015)","journal-title":"J. Optim. Theory Appl."},{"key":"1566_CR47","unstructured":"Schlueter, M., Munetomo, M.: Introduction to MIDACO-SOLVER software (2013)"},{"key":"1566_CR48","doi-asserted-by":"crossref","unstructured":"Holmstr\u00f6m, K., Edvall, M.M.: The TOMLAB optimization environment. Modeling Languages in Mathematical Optimization, 369\u2013376 (2004)","DOI":"10.1007\/978-1-4613-0215-5_19"},{"key":"1566_CR49","doi-asserted-by":"publisher","first-page":"611","DOI":"10.1007\/s10898-018-0640-3","volume":"74","author":"J Liu","year":"2019","unstructured":"Liu, J., Ploskas, N., Sahinidis, N.V.: Tuning BARON using derivative-free optimization algorithms. J. Global Optim. 74, 611\u2013637 (2019)","journal-title":"J. Global Optim."},{"issue":"3","key":"1566_CR50","doi-asserted-by":"publisher","first-page":"638","DOI":"10.1080\/10556788.2018.1527331","volume":"35","author":"B Sauk","year":"2020","unstructured":"Sauk, B., Ploskas, N., Sahinidis, N.: GPU parameter tuning for tall and skinny dense linear least squares problems. Optim. Methods Softw. 35(3), 638\u2013660 (2020)","journal-title":"Optim. Methods Softw."},{"issue":"5","key":"1566_CR51","doi-asserted-by":"publisher","first-page":"743","DOI":"10.1016\/j.advwatres.2008.01.010","volume":"31","author":"KR Fowler","year":"2008","unstructured":"Fowler, K.R., Reese, J.P., Kees, C.E., Dennis, J., Jr., Kelley, C.T., Miller, C.T., Audet, C., Booker, A.J., Couture, G., Darwin, R.W., et al.: Comparison of derivative-free optimization methods for groundwater supply and hydraulic capture community problems. Adv. Water Resour. 31(5), 743\u2013757 (2008)","journal-title":"Adv. Water Resour."},{"key":"1566_CR52","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1016\/j.cherd.2017.05.015","volume":"131","author":"N Ploskas","year":"2018","unstructured":"Ploskas, N., Laughman, C., Raghunathan, A.U., Sahinidis, N.V.: Optimization of circuitry arrangements for heat exchangers using derivative-free optimization. Chem. Eng. Res. Des. 131, 16\u201328 (2018)","journal-title":"Chem. Eng. Res. Des."},{"issue":"1","key":"1566_CR53","doi-asserted-by":"publisher","first-page":"1301","DOI":"10.1016\/j.procs.2010.04.145","volume":"1","author":"DE Ciaurri","year":"2010","unstructured":"Ciaurri, D.E., Isebor, O.J., Durlofsky, L.J.: Application of derivative-free methodologies to generally constrained oil production optimization problems. Procedia Comput. Sci. 1(1), 1301\u20131310 (2010)","journal-title":"Procedia Comput. Sci."},{"key":"1566_CR54","doi-asserted-by":"publisher","first-page":"98","DOI":"10.1016\/j.coche.2019.11.006","volume":"27","author":"Y Sun","year":"2020","unstructured":"Sun, Y., Sahinidis, N.V., Sundaram, A., Cheon, M.-S.: Derivative-free optimization for chemical product design. Curr. Opin. Chem. Eng. 27, 98\u2013106 (2020)","journal-title":"Curr. Opin. Chem. Eng."},{"key":"1566_CR55","doi-asserted-by":"publisher","DOI":"10.1016\/j.compchemeng.2024.108584","volume":"182","author":"A Durkin","year":"2024","unstructured":"Durkin, A., Otte, L., Guo, M.: Surrogate-based optimisation of process systems to recover resources from wastewater. Comput. Chem. Eng. 182, 108584 (2024)","journal-title":"Comput. Chem. Eng."},{"issue":"3","key":"1566_CR56","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3338517","volume":"45","author":"C Cartis","year":"2019","unstructured":"Cartis, C., Fiala, J., Marteau, B., Roberts, L.: Improving the flexibility and robustness of model-based derivative-free optimization solvers. ACM Trans. Math. Softw. (TOMS) 45(3), 1\u201341 (2019)","journal-title":"ACM Trans. Math. Softw. (TOMS)"},{"issue":"2","key":"1566_CR57","doi-asserted-by":"publisher","first-page":"233","DOI":"10.1109\/TSMCC.2004.841906","volume":"35","author":"TP Runarsson","year":"2005","unstructured":"Runarsson, T.P., Yao, X.: Search biases in constrained evolutionary optimization. IEEE Trans. Syst. Man Cybern. Part C (Appl. Rev.) 35(2), 233\u2013243 (2005)","journal-title":"IEEE Trans. Syst. Man Cybern. Part C (Appl. Rev.)"},{"key":"1566_CR58","unstructured":"Inc., T.M.: MATLAB Version: 9.13.0 (R2022b). https:\/\/www.mathworks.com"},{"issue":"5","key":"1566_CR59","doi-asserted-by":"publisher","first-page":"1383","DOI":"10.1016\/j.cor.2012.08.022","volume":"40","author":"J M\u00fcller","year":"2013","unstructured":"M\u00fcller, J., Shoemaker, C.A., Pich\u00e9, R.: SO-MI: a surrogate model algorithm for computationally expensive nonlinear mixed-integer black-box global optimization problems. Comput. Oper. Res. 40(5), 1383\u20131400 (2013)","journal-title":"Comput. Oper. Res."},{"key":"1566_CR60","doi-asserted-by":"crossref","unstructured":"Sainvitu, C., Iliopoulou, V., Lepot, I.: Global optimization with expensive functions-sample turbomachinery design application. In: Recent Advances in Optimization and Its Applications in Engineering: The 14th Belgian-French-German Conference on Optimization, pp. 499\u2013509 (2010). Springer","DOI":"10.1007\/978-3-642-12598-0_44"},{"key":"1566_CR61","doi-asserted-by":"crossref","unstructured":"Ploskas, N.: Parameter tuning of linear programming solvers. In: 2022 7th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM), pp. 1\u20136 (2022). IEEE","DOI":"10.1109\/SEEDA-CECNSM57760.2022.9933002"},{"key":"1566_CR62","doi-asserted-by":"publisher","first-page":"611","DOI":"10.1007\/s10898-018-0640-3","volume":"74","author":"J Liu","year":"2019","unstructured":"Liu, J., Ploskas, N., Sahinidis, N.V.: Tuning BARON using derivative-free optimization algorithms. J. Global Optim. 74, 611\u2013637 (2019)","journal-title":"J. Global Optim."},{"key":"1566_CR63","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1613\/jair.2861","volume":"36","author":"F Hutter","year":"2009","unstructured":"Hutter, F., Hoos, H.H., Leyton-Brown, K., St\u00fctzle, T.: ParamILS: an automatic algorithm configuration framework. J. Artif. Intell. Res. 36, 267\u2013306 (2009)","journal-title":"J. Artif. Intell. Res."},{"issue":"2","key":"1566_CR64","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1007\/s10472-022-09793-3","volume":"91","author":"B Sauk","year":"2023","unstructured":"Sauk, B., Sahinidis, N.V.: Hyperparameter autotuning of programs with HybridTuner. Ann. Math. Artif. Intell. 91(2), 133\u2013151 (2023)","journal-title":"Ann. Math. Artif. Intell."},{"key":"1566_CR65","doi-asserted-by":"crossref","unstructured":"Sauk, B., Sahinidis, N.V.: HybridTuner: Tuning with hybrid derivative-free optimization initialization strategies. In: International Conference on Learning and Intelligent Optimization, pp. 379\u2013393 (2021). Springer","DOI":"10.1007\/978-3-030-92121-7_29"},{"key":"1566_CR66","doi-asserted-by":"crossref","unstructured":"Tapus, C., Chung, I.-H., Hollingsworth, J.K.: Active harmony: Towards automated performance tuning. In: SC\u201902: Proceedings of the 2002 ACM\/IEEE Conference on Supercomputing, pp. 44\u201344 (2002). IEEE","DOI":"10.1109\/SC.2002.10062"},{"key":"1566_CR67","doi-asserted-by":"crossref","unstructured":"Ansel, J., Kamil, S., Veeramachaneni, K., Ragan-Kelley, J., Bosboom, J., O\u2019Reilly, U.-M., Amarasinghe, S.: OpenTuner: An extensible framework for program autotuning. In: Proceedings of the 23rd International Conference on Parallel Architectures and Compilation, pp. 303\u2013316 (2014)","DOI":"10.1145\/2628071.2628092"},{"key":"1566_CR68","doi-asserted-by":"crossref","unstructured":"Hu, Y.-Q., Liu, Z., Yang, H., Yu, Y., Liu, Y.: Derivative-free optimization with adaptive experience for efficient hyper-parameter tuning. In: European Conference on Artificial Intelligence (2020). https:\/\/api.semanticscholar.org\/CorpusID:221714376","DOI":"10.3233\/FAIA200220"},{"key":"1566_CR69","doi-asserted-by":"crossref","unstructured":"Kudva, A., Sorouifar, F., Paulson, J.A.: Efficient robust global optimization for simulation-based problems using decomposed gaussian processes: Application to MPC calibration. In: 2022 American Control Conference (ACC), pp. 2091\u20132097 (2022). IEEE","DOI":"10.23919\/ACC53348.2022.9867777"},{"key":"1566_CR70","doi-asserted-by":"publisher","unstructured":"Audet, C., Dang, C.-K., Orban, D.: In: Naono, K., Teranishi, K., Cavazos, J., Suda, R. (eds.) Algorithmic Parameter Optimization of the DFO Method with the OPAL Framework, pp. 255\u2013274. Springer, New York, NY (2010). https:\/\/doi.org\/10.1007\/978-1-4419-6935-4_15","DOI":"10.1007\/978-1-4419-6935-4_15"},{"key":"1566_CR71","doi-asserted-by":"publisher","first-page":"785","DOI":"10.1016\/j.compchemeng.2017.02.010","volume":"106","author":"ZT Wilson","year":"2017","unstructured":"Wilson, Z.T., Sahinidis, N.V.: The ALAMO approach to machine learning. Comput. Chem. Eng. 106, 785\u2013795 (2017)","journal-title":"Comput. Chem. Eng."},{"issue":"2","key":"1566_CR72","doi-asserted-by":"publisher","first-page":"201","DOI":"10.1007\/BF00138693","volume":"8","author":"NV Sahinidis","year":"1996","unstructured":"Sahinidis, N.V.: BARON: a general purpose global optimization software package. J. Global Optim. 8(2), 201\u2013205 (1996)","journal-title":"J. Global Optim."},{"key":"1566_CR73","unstructured":"Huyer, W., Neumaier, A.: Benchmarking of SNOBFIT on the noisy function testbed. Online, 2009a. URL http:\/\/www.mat.univie.ac.at\/~neum\/papers.html, 987 (2009)"},{"issue":"2","key":"1566_CR74","doi-asserted-by":"publisher","first-page":"293","DOI":"10.1007\/s10589-022-00363-1","volume":"82","author":"T Giovannelli","year":"2022","unstructured":"Giovannelli, T., Liuzzi, G., Lucidi, S., Rinaldi, F.: Derivative-free methods for mixed-integer nonsmooth constrained optimization. Comput. Optim. Appl. 82(2), 293\u2013327 (2022)","journal-title":"Comput. Optim. Appl."}],"container-title":["Journal of Global Optimization"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10898-025-01566-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10898-025-01566-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10898-025-01566-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,17]],"date-time":"2025-12-17T07:02:52Z","timestamp":1765954972000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10898-025-01566-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12]]},"references-count":74,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2025,12]]}},"alternative-id":["1566"],"URL":"https:\/\/doi.org\/10.1007\/s10898-025-01566-6","relation":{},"ISSN":["0925-5001","1573-2916"],"issn-type":[{"type":"print","value":"0925-5001"},{"type":"electronic","value":"1573-2916"}],"subject":[],"published":{"date-parts":[[2025,12]]},"assertion":[{"value":"29 July 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 November 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 December 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}