{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,29]],"date-time":"2025-09-29T20:44:35Z","timestamp":1759178675444},"publisher-location":"Cham","reference-count":18,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319992525"},{"type":"electronic","value":"9783319992532"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-319-99253-2_2","type":"book-chapter","created":{"date-parts":[[2018,8,21]],"date-time":"2018-08-21T06:14:41Z","timestamp":1534832081000},"page":"16-28","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Design of a Surrogate Model Assisted (1\u00a0+\u00a01)-ES"],"prefix":"10.1007","author":[{"given":"Arash","family":"Kayhani","sequence":"first","affiliation":[]},{"given":"Dirk V.","family":"Arnold","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,8,22]]},"reference":[{"key":"2_CR1","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4615-1105-2","volume-title":"Noisy Optimization with Evolution Strategies","author":"DV Arnold","year":"2002","unstructured":"Arnold, D.V.: Noisy Optimization with Evolution Strategies. Kluwer, Dordrecht (2002)"},{"issue":"4","key":"2_CR2","doi-asserted-by":"publisher","first-page":"380","DOI":"10.1109\/TEVC.2005.859467","volume":"10","author":"DV Arnold","year":"2006","unstructured":"Arnold, D.V., Beyer, H.-G.: A general noise model and its effects on evolution strategy performance. IEEE Trans. Evol. Comput. 10(4), 380\u2013391 (2006)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"2_CR3","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/978-3-642-02011-7_3","volume-title":"Experimental Algorithms","author":"A Auger","year":"2009","unstructured":"Auger, A., Hansen, N., Perez Zerpa, J.M., Ros, R., Schoenauer, M.: Experimental comparisons of derivative free optimization algorithms. In: Vahrenhold, J. (ed.) SEA 2009. LNCS, vol. 5526, pp. 3\u201315. Springer, Heidelberg (2009). https:\/\/doi.org\/10.1007\/978-3-642-02011-7_3"},{"issue":"2","key":"2_CR4","doi-asserted-by":"publisher","first-page":"183","DOI":"10.1109\/TSMCC.2004.841917","volume":"35","author":"D B\u00fcche","year":"2005","unstructured":"B\u00fcche, D., Schraudolph, N.N., Koumoutsakos, P.: Accelerating evolutionary algorithms with Gaussian process fitness function models. IEEE Trans. Syst. Man Cybern. B Cybern. Part C 35(2), 183\u2013194 (2005)","journal-title":"IEEE Trans. Syst. Man Cybern. B Cybern. Part C"},{"key":"2_CR5","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1007\/978-3-319-09333-8_4","volume-title":"Intelligent Computing Theory","author":"Y Chen","year":"2014","unstructured":"Chen, Y., Zou, X.: Performance analysis of a (1+1) surrogate-assisted evolutionary algorithm. In: Huang, D.-S., Bevilacqua, V., Premaratne, P. (eds.) ICIC 2014. LNCS, vol. 8588, pp. 32\u201340. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-09333-8_4"},{"key":"2_CR6","doi-asserted-by":"publisher","first-page":"871","DOI":"10.1007\/978-3-662-43505-2_44","volume-title":"Springer Handbook of Computational Intelligence","author":"N Hansen","year":"2015","unstructured":"Hansen, N., Arnold, D.V., Auger, A.: Evolution strategies. In: Kacprzyk, J., Pedrycz, W. (eds.) Springer Handbook of Computational Intelligence, pp. 871\u2013898. Springer, Heidelberg (2015). https:\/\/doi.org\/10.1007\/978-3-662-43505-2_44"},{"issue":"2","key":"2_CR7","doi-asserted-by":"publisher","first-page":"159","DOI":"10.1162\/106365601750190398","volume":"9","author":"N Hansen","year":"2001","unstructured":"Hansen, N., Ostermeier, A.: Completely derandomized self-adaptation in evolution strategies. Evol. Comput. 9(2), 159\u2013195 (2001)","journal-title":"Evol. Comput."},{"issue":"2","key":"2_CR8","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1016\/j.swevo.2011.05.001","volume":"1","author":"Y Jin","year":"2011","unstructured":"Jin, Y.: Surrogate-assisted evolutionary computation: recent advances and future challenges. Swarm Evol. Comput. 1(2), 61\u201370 (2011)","journal-title":"Swarm Evol. Comput."},{"key":"2_CR9","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"939","DOI":"10.1007\/11844297_95","volume-title":"Parallel Problem Solving from Nature - PPSN IX","author":"S Kern","year":"2006","unstructured":"Kern, S., Hansen, N., Koumoutsakos, P.: Local meta-models for optimization using evolution strategies. In: Runarsson, T.P., Beyer, H.-G., Burke, E., Merelo-Guerv\u00f3s, J.J., Whitley, L.D., Yao, X. (eds.) PPSN 2006. LNCS, vol. 4193, pp. 939\u2013948. Springer, Heidelberg (2006). https:\/\/doi.org\/10.1007\/11844297_95"},{"issue":"1","key":"2_CR10","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1023\/B:NACO.0000023416.59689.4e","volume":"3","author":"S Kern","year":"2004","unstructured":"Kern, S., M\u00fcller, S.D., Hansen, N., B\u00fcche, D., Ocenasek, J., Koumoutsakos, P.: Learning probability distributions in continuous evolutionary algorithms \u2013 a comparative review. Nat. Comput. 3(1), 77\u2013112 (2004)","journal-title":"Nat. Comput."},{"key":"2_CR11","unstructured":"Loshchilov, I.: Surrogate-Assisted Evolutionary Algorithms. PhD thesis, Universit\u00e9 Paris Sud - Paris XI (2013)"},{"key":"2_CR12","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"364","DOI":"10.1007\/978-3-642-15844-5_37","volume-title":"Parallel Problem Solving from Nature, PPSN XI","author":"I Loshchilov","year":"2010","unstructured":"Loshchilov, I., Schoenauer, M., Sebag, M.: Comparison-based optimizers need comparison-based surrogates. In: Schaefer, R., Cotta, C., Ko\u0142odziej, J., Rudolph, G. (eds.) PPSN 2010. LNCS, vol. 6238, pp. 364\u2013373. Springer, Heidelberg (2010). https:\/\/doi.org\/10.1007\/978-3-642-15844-5_37"},{"key":"2_CR13","doi-asserted-by":"crossref","unstructured":"Loshchilov, I., Schoenauer, M., Sebag, M.: Intensive surrogate model exploitation in self-adaptive surrogate-assisted CMA-ES. In: Genetic and Evolutionary Computation Conference \u2013 GECCO 2013, pp. 439\u2013446. ACM Press (2013)","DOI":"10.1145\/2463372.2463427"},{"key":"2_CR14","doi-asserted-by":"crossref","unstructured":"Pitra, Z., Bajer, L., Repick\u00fd, J., Holena, M.: Overview of surrogate-model versions of covariance matrix adaptation evolution strategy. In: Genetic and Evolutionary Computation Conference Companion, pp. 1622\u20131629. ACM Press (2017)","DOI":"10.1145\/3067695.3082539"},{"key":"2_CR15","volume-title":"Evolutionsstrategie - Optimierung technischer Systeme nach Prinzipien der biologischen Evolution","author":"I Rechenberg","year":"1973","unstructured":"Rechenberg, I.: Evolutionsstrategie - Optimierung technischer Systeme nach Prinzipien der biologischen Evolution. Friedrich Frommann Verlag, Stuttgart (1973)"},{"key":"2_CR16","volume-title":"Numerical Optimization of Computer Models","author":"H-P Schwefel","year":"1981","unstructured":"Schwefel, H.-P.: Numerical Optimization of Computer Models. Wiley, Hoboken (1981)"},{"key":"2_CR17","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1007\/11844297_3","volume-title":"Parallel Problem Solving from Nature - PPSN IX","author":"O Teytaud","year":"2006","unstructured":"Teytaud, O., Gelly, S.: General lower bounds for evolutionary algorithms. In: Runarsson, T.P., Beyer, H.-G., Burke, E., Merelo-Guerv\u00f3s, J.J., Whitley, L.D., Yao, X. (eds.) PPSN 2006. LNCS, vol. 4193, pp. 21\u201331. Springer, Heidelberg (2006). https:\/\/doi.org\/10.1007\/11844297_3"},{"key":"2_CR18","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"610","DOI":"10.1007\/3-540-45105-6_72","volume-title":"Genetic and Evolutionary Computation \u2014 GECCO 2003","author":"H Ulmer","year":"2003","unstructured":"Ulmer, H., Streichert, F., Zell, A.: Model-assisted steady-state evolution strategies. In: Cant\u00fa-Paz, E. (ed.) GECCO 2003. LNCS, vol. 2723, pp. 610\u2013621. Springer, Heidelberg (2003). https:\/\/doi.org\/10.1007\/3-540-45105-6_72"}],"container-title":["Lecture Notes in Computer Science","Parallel Problem Solving from Nature \u2013 PPSN XV"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-99253-2_2","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,10,22]],"date-time":"2019-10-22T13:29:28Z","timestamp":1571750968000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-99253-2_2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783319992525","9783319992532"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-99253-2_2","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2018]]}}}