{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T07:21:41Z","timestamp":1740122501318,"version":"3.37.3"},"reference-count":45,"publisher":"Springer Science and Business Media LLC","issue":"1-2","license":[{"start":{"date-parts":[[2016,2,26]],"date-time":"2016-02-26T00:00:00Z","timestamp":1456444800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2016,2,26]],"date-time":"2016-02-26T00:00:00Z","timestamp":1456444800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100000923","name":"Australian Research Council","doi-asserted-by":"publisher","award":["LP120200554"],"award-info":[{"award-number":["LP120200554"]}],"id":[{"id":"10.13039\/501100000923","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Glob Optim"],"published-print":{"date-parts":[[2017,1]]},"DOI":"10.1007\/s10898-016-0420-x","type":"journal-article","created":{"date-parts":[[2016,2,26]],"date-time":"2016-02-26T08:43:47Z","timestamp":1456476227000},"page":"263-282","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Dynamic algorithm selection for pareto optimal set approximation"],"prefix":"10.1007","volume":"67","author":[{"given":"Ingrida","family":"Steponavi\u010d\u0117","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rob J.","family":"Hyndman","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kate","family":"Smith-Miles","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Laura","family":"Villanova","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2016,2,26]]},"reference":[{"issue":"1","key":"420_CR1","doi-asserted-by":"publisher","first-page":"45","DOI":"10.1162\/EVCO_a_00009","volume":"19","author":"J Bader","year":"2011","unstructured":"Bader, J., Zitzler, E.: Hype: an algorithm for fast hypervolume-based many-objective optimization. Evol Comput 19(1), 45\u201376 (2011)","journal-title":"Evol Comput"},{"key":"420_CR2","doi-asserted-by":"crossref","unstructured":"Borrett, J.E., Tsang, E.P.: Adaptive constraint satisfaction: the quickest first principle. In: Computational Intelligence, pp. 203\u2013230. Springer (2009)","DOI":"10.1007\/978-3-642-01799-5_7"},{"issue":"1","key":"420_CR3","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman, L.: Random forests. Mach. Learn. 45(1), 5\u201332 (2001)","journal-title":"Mach. Learn."},{"key":"420_CR4","volume-title":"Multi-objective Optimization Using Evolutionary Algorithms","author":"K Deb","year":"2001","unstructured":"Deb, K.: Multi-objective Optimization Using Evolutionary Algorithms, vol. 16. Wiley, New York (2001)"},{"issue":"2","key":"420_CR5","doi-asserted-by":"publisher","first-page":"182","DOI":"10.1109\/4235.996017","volume":"6","author":"K Deb","year":"2002","unstructured":"Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans. Evol. Comput. 6(2), 182\u2013197 (2002)","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"10","key":"420_CR6","doi-asserted-by":"publisher","first-page":"760","DOI":"10.1016\/j.advengsoft.2011.05.014","volume":"42","author":"JJ Durillo","year":"2011","unstructured":"Durillo, J.J., Nebro, A.J.: jMetal: a java framework for multi-objective optimization. Adv. Eng. Softw. 42(10), 760\u2013771 (2011)","journal-title":"Adv. Eng. Softw."},{"key":"420_CR7","unstructured":"Feng, Z., Zhang, Q., Zhang, Q., Tang, Q., Yang, T., Ma, Y.: A multiobjective optimization based framework to balance the global exploration and local exploitation in expensive optimization. J. Glob. Optim. 61, 677\u2013694 (2014)"},{"issue":"1\u20133","key":"420_CR8","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1016\/j.paerosci.2008.11.001","volume":"45","author":"AI Forrester","year":"2009","unstructured":"Forrester, A.I., Keane, A.J.: Recent advances in surrogate-based optimization. Prog. Aerosp. Sci. 45(1\u20133), 50\u201379 (2009)","journal-title":"Prog. Aerosp. Sci."},{"issue":"1","key":"420_CR9","doi-asserted-by":"publisher","first-page":"259","DOI":"10.1007\/s10589-010-9329-3","volume":"51","author":"F Gao","year":"2012","unstructured":"Gao, F., Han, L.: Implementing the Nelder\u2013Mead simplex algorithm with adaptive parameters. Comput. Optim. Appl. 51(1), 259\u2013277 (2012)","journal-title":"Comput. Optim. Appl."},{"key":"420_CR10","doi-asserted-by":"crossref","unstructured":"Garrett, D., Dasgupta, D.: Multiobjective landscape analysis and the generalized assignment problem. In: Learning and Intelligent Optimization, pp. 110\u2013124. Springer (2008)","DOI":"10.1007\/978-3-540-92695-5_9"},{"issue":"1","key":"420_CR11","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1080\/10556780512331318290","volume":"21","author":"L Han","year":"2006","unstructured":"Han, L., Neumann, M.: Effect of dimensionality on the Nelder\u2013Mead simplex method. Optim. Methods Softw. 21(1), 1\u201316 (2006)","journal-title":"Optim. Methods Softw."},{"issue":"12","key":"420_CR12","doi-asserted-by":"publisher","first-page":"2391","DOI":"10.1109\/TCYB.2014.2307319","volume":"44","author":"S Jiang","year":"2014","unstructured":"Jiang, S., Ong, Y.S., Zhang, J., Feng, L.: Consistencies and contradictions of performance metrics in multiobjective optimization. IEEE Trans. Cybern. 44(12), 2391\u20132404 (2014)","journal-title":"IEEE Trans. Cybern."},{"issue":"1","key":"420_CR13","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s00158-001-0160-4","volume":"23","author":"R Jin","year":"2001","unstructured":"Jin, R., Chen, W., Simpson, T.: Comparative studies of metamodelling techniques under multiple modelling criteria. Struct. Multidiscip. Optim. 23(1), 1\u201313 (2001)","journal-title":"Struct. Multidiscip. Optim."},{"issue":"4","key":"420_CR14","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. Glob. Optim. 13(4), 455\u2013492 (1998)","journal-title":"J. Glob. Optim."},{"key":"420_CR15","unstructured":"Kaelbling, L.P., Littman, M.L., Moore, A.W.: Reinforcement learning: a survey. J. Artif. Intell. Res. 4, 237\u2013285 (1996)"},{"issue":"1","key":"420_CR16","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1109\/TEVC.2005.851274","volume":"10","author":"J Knowles","year":"2006","unstructured":"Knowles, J.: Parego: a hybrid algorithm with on-line landscape approximation for expensive multiobjective optimization problems. IEEE Trans. Evol. Comput. 10(1), 50\u201366 (2006)","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"5","key":"420_CR17","doi-asserted-by":"publisher","first-page":"572","DOI":"10.1109\/TEVC.2008.917202","volume":"12","author":"P Koduru","year":"2008","unstructured":"Koduru, P., Dong, Z., Das, S., Welch, S.M., Roe, J.L., Charbit, E.: A multiobjective evolutionary-simplex hybrid approach for the optimization of differential equation models of gene networks. IEEE Trans. Evol. Comput. 12(5), 572\u2013590 (2008)","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"3","key":"420_CR18","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":"420_CR19","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1007\/BFb0029752","volume-title":"Parallel Problem Solving from Nature","author":"F Kursawe","year":"1991","unstructured":"Kursawe, F.: A variant of evolution strategies for vector optimization. In: Schwefel, H.P., Mnner, R. (eds.) Parallel Problem Solving from Nature, vol. 496, pp. 193\u2013197. Springer, Berlin (1991)"},{"issue":"1","key":"420_CR20","doi-asserted-by":"publisher","first-page":"112","DOI":"10.1137\/S1052623496303470","volume":"9","author":"JC Lagarias","year":"1998","unstructured":"Lagarias, J.C., Reeds, J.A., Wright, M.H., Wright, P.E.: Convergence properties of the Nelder\u2013Mead simplex method in low dimensions. SIAM J. Optim. 9(1), 112\u2013147 (1998)","journal-title":"SIAM J. Optim."},{"key":"420_CR21","unstructured":"Lagoudakis, M.G., Littman, M.L.: Algorithm selection using reinforcement learning. In: ICML, pp. 511\u2013518. Citeseer (2000)"},{"issue":"23","key":"420_CR22","doi-asserted-by":"publisher","first-page":"2251","DOI":"10.1016\/j.compstruc.2004.03.072","volume":"82","author":"MA Luersen","year":"2004","unstructured":"Luersen, M.A., Le Riche, R.: Globalized Nelder\u2013Mead method for engineering optimization. Comput. Struct. 82(23), 2251\u20132260 (2004)","journal-title":"Comput. Struct."},{"issue":"6","key":"420_CR23","doi-asserted-by":"publisher","first-page":"369","DOI":"10.1007\/s00158-003-0368-6","volume":"26","author":"RT Marler","year":"2004","unstructured":"Marler, R.T., Arora, J.S.: Survey of multi-objective optimization methods for engineering. Struct. Multidiscip. Optim. 26(6), 369\u2013395 (2004)","journal-title":"Struct. Multidiscip. Optim."},{"key":"420_CR24","volume-title":"Nonlinear Multiobjective Optimization","author":"K Miettinen","year":"1999","unstructured":"Miettinen, K.: Nonlinear Multiobjective Optimization, vol. 12. Springer Science & Business Media, Berlin (1999)"},{"key":"420_CR25","doi-asserted-by":"publisher","DOI":"10.1007\/978-94-009-0909-0","volume-title":"Bayesian Approach to Global Optimization","author":"J Mockus","year":"1989","unstructured":"Mockus, J.: Bayesian Approach to Global Optimization. Kluwer Academic Publishers, Dordrecht (1989)"},{"issue":"4","key":"420_CR26","doi-asserted-by":"publisher","first-page":"308","DOI":"10.1093\/comjnl\/7.4.308","volume":"7","author":"JA Nelder","year":"1965","unstructured":"Nelder, J.A., Mead, R.: A simplex method for function minimization. Comput. J. 7(4), 308\u2013313 (1965)","journal-title":"Comput. J."},{"key":"420_CR27","doi-asserted-by":"publisher","first-page":"792","DOI":"10.1007\/978-3-540-30217-9_80","volume-title":"Parallel Problem Solving from Nature\u2014PPSN VIII","author":"T Okabe","year":"2011","unstructured":"Okabe, T., Jin, Y., Sendhoff, M.O.B.: On test functions for evolutionary multi-objective optimization. In: Yao, X., Burke, E., Lozano, J., Smith, J., Merelo-Guervs, J., Bullinaria, J., Rowe, J., Tio, P., Kabn, A., Schwefel, H.P. (eds.) Parallel Problem Solving from Nature\u2014PPSN VIII, vol. 3242, pp. 792\u2013802. Springer, Berlin (2011)"},{"issue":"3","key":"420_CR28","first-page":"55","volume":"3","author":"N Pham","year":"2011","unstructured":"Pham, N., Wilamowski, B.M.: Improved Nelder Meads simplex method and applications. J. Comput. 3(3), 55\u201363 (2011)","journal-title":"J. Comput."},{"key":"420_CR29","doi-asserted-by":"publisher","first-page":"784","DOI":"10.1007\/978-3-540-87700-4_78","volume-title":"Parallel Problem Solving from Nature\u2014PPSN X","author":"W Ponweiser","year":"2008","unstructured":"Ponweiser, W., Wagner, T., Biermann, D., Vincze, M.: Multiobjective optimization on a limited budget of evaluations using model-assisted $$\\cal {S}$$-metric selection. In: Rudolph, G., Jansen, T., Beume, N., Lucas, S., Poloni, C. (eds.) Parallel Problem Solving from Nature\u2014PPSN X, vol. 5199, pp. 784\u2013794. Springer, Berlin (2008)"},{"key":"420_CR30","unstructured":"Rice, J.R.: The algorithm selection problem. Comput. Sci. Tech. Rep. (1975). \n                    http:\/\/docs.lib.purdue.edu\/cstech\/99"},{"key":"420_CR31","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1007\/978-3-642-10701-6_2","volume-title":"Computational Intelligence in Expensive Optimization Problems","author":"L Santana-Quintero","year":"2010","unstructured":"Santana-Quintero, L., Monta\u00f1o, A., Coello, C.C.: A review of techniques for handling expensive functions in evolutionary multi-objective optimization. In: Tenne, Y., Goh, C.K. (eds.) Computational Intelligence in Expensive Optimization Problems, vol. 2, pp. 29\u201359. Springer, Berlin (2010)"},{"key":"420_CR32","doi-asserted-by":"crossref","unstructured":"Steponavi\u010d\u0117, I., Hyndman, R.J., Smith-Miles, K., Villanova, L.: Efficient identification of the Pareto optimal set. In: Learning and Intelligent Optimization, pp. 341\u2013352. Springer International Publishing (2014)","DOI":"10.1007\/978-3-319-09584-4_29"},{"key":"420_CR33","unstructured":"Torczon, V.J.: Multi-directional search: a direct search algorithm for parallel machines. Ph.D. thesis, Citeseer (1989)"},{"key":"420_CR34","doi-asserted-by":"crossref","unstructured":"T\u00f6rn, A., \u017dilinskas, A.: Global Optimization. Springer, New York, NY (1989)","DOI":"10.1007\/3-540-50871-6"},{"key":"420_CR35","doi-asserted-by":"crossref","unstructured":"Van Veldhuizen, D.A., Lamont, G.B.: Multiobjective evolutionary algorithm test suites. In: Proceedings of the 1999 ACM Symposium on Applied Computing, pp. 351\u2013357. ACM (1999)","DOI":"10.1145\/298151.298382"},{"key":"420_CR36","doi-asserted-by":"crossref","unstructured":"Viennet, R., Fonteix, C., Marc, I.: New multicriteria optimization method based on the use of a diploid genetic algorithm: example of an industrial problem. In: Selected Papers from the European Conference on Artificial Evolution, pp. 120\u2013127. Springer, London (1996)","DOI":"10.1007\/3-540-61108-8_34"},{"key":"420_CR37","volume-title":"Planning and Multi-objective Optimization of Manufacturing Processes by Means of Empirical Surrogate Models","author":"T Wagner","year":"2013","unstructured":"Wagner, T.: Planning and Multi-objective Optimization of Manufacturing Processes by Means of Empirical Surrogate Models. Vulkan, Essen (2013)"},{"issue":"1","key":"420_CR38","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1115\/1.1329875","volume":"123","author":"J Wu","year":"2001","unstructured":"Wu, J., Azarm, S.: Metrics for quality assessment of a multiobjective design optimization solution set. J. Mech. Des. 123(1), 18\u201325 (2001)","journal-title":"J. Mech. Des."},{"issue":"2","key":"420_CR39","doi-asserted-by":"publisher","first-page":"3880","DOI":"10.1016\/j.eswa.2008.02.039","volume":"36","author":"E Zahara","year":"2009","unstructured":"Zahara, E., Kao, Y.T.: Hybrid Nelder\u2013Mead simplex search and particle swarm optimization for constrained engineering design problems. Expert Syst. Appl. 36(2), 3880\u20133886 (2009)","journal-title":"Expert Syst. Appl."},{"key":"420_CR40","doi-asserted-by":"crossref","unstructured":"Zapotecas-Mart\u00ednez, S., Coello, C.A.C.: Monss: a multi-objective nonlinear simplex search approach. Eng. Optim. 48, 16\u201338 (2016)","DOI":"10.1080\/0305215X.2014.992889"},{"issue":"3","key":"420_CR41","doi-asserted-by":"publisher","first-page":"456","DOI":"10.1109\/TEVC.2009.2033671","volume":"14","author":"Q Zhang","year":"2010","unstructured":"Zhang, Q., Liu, W., Tsang, E., Virginas, B.: Expensive multiobjective optimization by MOEA\/D with Gaussian process model. IEEE Trans. Evol. Comput. 14(3), 456\u2013474 (2010)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"420_CR42","doi-asserted-by":"crossref","unstructured":"Zitzler, E., Brockhoff, D., Thiele, L.: The hypervolume indicator revisited: On the design of Pareto-compliant indicators via weighted integration. In: Evolutionary Multi-criterion Optimization, pp. 862\u2013876. Springer (2007)","DOI":"10.1007\/978-3-540-70928-2_64"},{"issue":"2","key":"420_CR43","doi-asserted-by":"publisher","first-page":"173","DOI":"10.1162\/106365600568202","volume":"8","author":"E Zitzler","year":"2000","unstructured":"Zitzler, E., Deb, K., Thiele, L.: Comparison of multiobjective evolutionary algorithms: empirical results. Evol. Comput. 8(2), 173\u2013195 (2000)","journal-title":"Evol. Comput."},{"key":"420_CR44","doi-asserted-by":"crossref","unstructured":"Zitzler, E., Thiele, L.: Multiobjective optimization using evolutionary algorithms\u2014a comparative case study. In: Parallel Problem Solving from Nature\u2014PPSN-V, pp. 292\u2013301. Springer (1998)","DOI":"10.1007\/BFb0056872"},{"issue":"2","key":"420_CR45","doi-asserted-by":"publisher","first-page":"117","DOI":"10.1109\/TEVC.2003.810758","volume":"7","author":"E Zitzler","year":"2003","unstructured":"Zitzler, E., Thiele, L., Laumanns, M., Fonseca, C.M., Da Fonseca, V.G.: Performance assessment of multiobjective optimizers: an analysis and review. IEEE Trans. Evol. Comput. 7(2), 117\u2013132 (2003)","journal-title":"IEEE Trans. Evol. Comput."}],"container-title":["Journal of Global Optimization"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10898-016-0420-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10898-016-0420-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10898-016-0420-x","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10898-016-0420-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,5,17]],"date-time":"2020-05-17T07:24:00Z","timestamp":1589700240000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10898-016-0420-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,2,26]]},"references-count":45,"journal-issue":{"issue":"1-2","published-print":{"date-parts":[[2017,1]]}},"alternative-id":["420"],"URL":"https:\/\/doi.org\/10.1007\/s10898-016-0420-x","relation":{},"ISSN":["0925-5001","1573-2916"],"issn-type":[{"type":"print","value":"0925-5001"},{"type":"electronic","value":"1573-2916"}],"subject":[],"published":{"date-parts":[[2016,2,26]]},"assertion":[{"value":"26 April 2015","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 February 2016","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 February 2016","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}