{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T14:37:41Z","timestamp":1742913461949,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":34,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819635375"},{"type":"electronic","value":"9789819635382"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"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":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-981-96-3538-2_11","type":"book-chapter","created":{"date-parts":[[2025,2,28]],"date-time":"2025-02-28T12:58:09Z","timestamp":1740747489000},"page":"147-162","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Mixed-Fidelity Evaluation Algorithm for\u00a0Efficient Constrained Multi- and\u00a0Many-Objective Optimization: First Results"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4829-148X","authenticated-orcid":false,"given":"Balija","family":"Santoshkumar","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7402-9939","authenticated-orcid":false,"given":"Kalyanmoy","family":"Deb","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,2,28]]},"reference":[{"issue":"2","key":"11_CR1","doi-asserted-by":"publisher","first-page":"497","DOI":"10.1016\/j.ejor.2014.09.033","volume":"243","author":"R Allmendinger","year":"2015","unstructured":"Allmendinger, R., Handl, J., Knowles, J.: Multiobjective optimization: when objectives exhibit non-uniform latencies. Eur. J. Oper. Res. 243(2), 497\u2013513 (2015)","journal-title":"Eur. J. Oper. Res."},{"key":"11_CR2","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"6","DOI":"10.1007\/978-3-642-37140-0_5","volume-title":"Evolutionary Multi-Criterion Optimization","author":"R Allmendinger","year":"2013","unstructured":"Allmendinger, R., Knowles, J.: \u2018Hang on a minute\u2019: investigations on the effects of delayed objective functions in multiobjective optimization. In: Purshouse, R.C., Fleming, P.J., Fonseca, C.M., Greco, S., Shaw, J. (eds.) EMO 2013. LNCS, vol. 7811, pp. 6\u201320. Springer, Heidelberg (2013). https:\/\/doi.org\/10.1007\/978-3-642-37140-0_5"},{"key":"11_CR3","doi-asserted-by":"publisher","unstructured":"Allmendinger, R., Knowles, J.: Heterogeneous objectives: state-of-the-art and future research. In: Many-Criteria Optimization and Decision Analysis: State-of-the-Art, Present Challenges, and Future Perspectives, pp. 317\u2013335. Springer (2023). https:\/\/doi.org\/10.1007\/978-3-031-25263-1_12","DOI":"10.1007\/978-3-031-25263-1_12"},{"key":"11_CR4","doi-asserted-by":"crossref","unstructured":"Blank, J., Deb, K.: Constrained bi-objective surrogate-assisted optimization of problems with heterogeneous evaluation times: expensive objectives and inexpensive constraints. In: EMO, pp. 257\u2013269 (2021)","DOI":"10.1007\/978-3-030-72062-9_21"},{"issue":"2","key":"11_CR5","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1007\/s12293-022-00362-z","volume":"14","author":"J Blank","year":"2022","unstructured":"Blank, J., Deb, K.: Handling constrained multi-objective optimization problems with heterogeneous evaluation times: proof-of-principle results. Memetic Comput. 14(2), 135\u2013150 (2022)","journal-title":"Memetic Comput."},{"key":"11_CR6","doi-asserted-by":"crossref","unstructured":"Blank, J., Deb, K.: pysamoo: Surrogate-assisted multi-objective optimization in python (2022)","DOI":"10.1145\/3449639.3459297"},{"key":"11_CR7","doi-asserted-by":"crossref","unstructured":"Blank, J., Deb, K., Dhebar, Y., Bandaru, S., Seada, H.: Generating well-spaced points on a unit simplex for evolutionary many-objective optimization. IEEE Trans. Evol. Comput. 25, 48\u201360 (2020)","DOI":"10.1109\/TEVC.2020.2992387"},{"issue":"1","key":"11_CR8","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1109\/TEVC.2016.2622301","volume":"22","author":"T Chugh","year":"2018","unstructured":"Chugh, T., Jin, Y., Miettinen, K., Hakanen, J., Sindhya, K.: A surrogate-assisted reference vector guided evolutionary algorithm for computationally expensive many-objective optimization. IEEE Trans. Evol. Comput. 22(1), 129\u2013142 (2018)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"11_CR9","doi-asserted-by":"publisher","first-page":"3137","DOI":"10.1007\/s00500-017-2965-0","volume":"23","author":"T Chugh","year":"2019","unstructured":"Chugh, T., Sindhya, K., Hakanen, J., Miettinen, K.: A survey on handling computationally expensive multiobjective optimization problems with evolutionary algorithms. Soft. Comput. 23, 3137\u20133166 (2019)","journal-title":"Soft. Comput."},{"issue":"3","key":"11_CR10","doi-asserted-by":"publisher","first-page":"631","DOI":"10.1137\/S1052623496307510","volume":"8","author":"I Das","year":"1998","unstructured":"Das, I., Dennis, J.: Normal-boundary intersection: a new method for generating the Pareto surface in nonlinear multicriteria optimization problems. SIAM J. Optim. 8(3), 631\u2013657 (1998)","journal-title":"SIAM J. Optim."},{"issue":"11","key":"11_CR11","doi-asserted-by":"publisher","first-page":"2013","DOI":"10.2514\/3.10834","volume":"29","author":"K Deb","year":"1991","unstructured":"Deb, K.: Optimal design of a welded beam via genetic algorithms. AIAA J. 29(11), 2013\u20132015 (1991)","journal-title":"AIAA J."},{"key":"11_CR12","unstructured":"Deb, K.: Multi-Objective Optimization Using Evolutionary Algorithms. Wiley, Chichester (2001)"},{"issue":"1","key":"11_CR13","doi-asserted-by":"publisher","first-page":"104","DOI":"10.1109\/TEVC.2018.2828091","volume":"23","author":"K Deb","year":"2019","unstructured":"Deb, K., Hussein, R., Roy, P., Toscano, G.: A taxonomy for metamodeling frameworks for evolutionary multi-objective optimization. IEEE Trans. Evol. Comput. 23(1), 104\u2013116 (2019)","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"4","key":"11_CR14","doi-asserted-by":"publisher","first-page":"577","DOI":"10.1109\/TEVC.2013.2281535","volume":"18","author":"K Deb","year":"2014","unstructured":"Deb, K., Jain, H.: An evolutionary many-objective optimization algorithm using reference-point based non-dominated sorting approach, Part I: Solving problems with box constraints. IEEE Trans. Evol. Comput. 18(4), 577\u2013601 (2014)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"11_CR15","doi-asserted-by":"publisher","unstructured":"Deb, K., Thiele, L., Laumanns, M., Zitzler, E.: Scalable test problems for evolutionary multi-objective optimization. In: Abraham, A., Jain, L., Goldberg, R. (eds.) Evolutionary Multiobjective Optimization, pp. 105\u2013145. Springer-Verlag, London (2005). https:\/\/doi.org\/10.1007\/1-84628-137-7_6","DOI":"10.1007\/1-84628-137-7_6"},{"issue":"1","key":"11_CR16","first-page":"5","volume":"26","author":"K Deb","year":"2020","unstructured":"Deb, K., Roy, P.C., Hussein, R.: Surrogate modeling approaches for multiobjective optimization: methods, taxonomy, and results. Math. Comput. Appl. 26(1), 5 (2020)","journal-title":"Math. Comput. Appl."},{"key":"11_CR17","doi-asserted-by":"crossref","unstructured":"Hussein, R., Deb, K.: A generative kriging surrogate model for constrained and unconstrained multi-objective optimization. In: Proceedings of the Genetic and Evolutionary Computation Conference 2016, pp. 573\u2013580 (2016)","DOI":"10.1145\/2908812.2908866"},{"issue":"4","key":"11_CR18","doi-asserted-by":"publisher","first-page":"602","DOI":"10.1109\/TEVC.2013.2281534","volume":"18","author":"H Jain","year":"2014","unstructured":"Jain, H., Deb, K.: An evolutionary many-objective optimization algorithm using reference-point based non-dominated sorting approach, Part II: Handling constraints and extending to an adaptive approach. IEEE Trans. Evol. Comput. 18(4), 602\u2013622 (2014)","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"2","key":"11_CR19","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."},{"issue":"1","key":"11_CR20","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 landscap e approximation for expensive multiobjective optimization problems. IEEE Trans. Evol. Comput. 10(1), 50\u201366 (2006)","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"6","key":"11_CR21","first-page":"119","volume":"52","author":"DG Krige","year":"1951","unstructured":"Krige, D.G.: A statistical approach to some basic mine valuation problems on the witwatersrand. J. South Afr. Inst. Min. Metall. 52(6), 119\u2013139 (1951)","journal-title":"J. South Afr. Inst. Min. Metall."},{"issue":"2","key":"11_CR22","doi-asserted-by":"publisher","first-page":"284","DOI":"10.1109\/TEVC.2008.925798","volume":"12","author":"H Li","year":"2009","unstructured":"Li, H., Zhang, Q.: Multiobjective optimization problems with complicated Pareto sets, MOEA\/D and NSGA-II. IEEE Trans. Evol. Comput. 12(2), 284\u2013302 (2009)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"11_CR23","unstructured":"Lophaven, S.N., Nielsen, H.B., Sondergaard, J., Dace, A.: A MATLAB kriging toolbox. Technical University of Denmark, Kongens Lyngby, Technical Report No. IMM-TR-2002-12 (2002)"},{"issue":"6","key":"11_CR24","doi-asserted-by":"publisher","first-page":"972","DOI":"10.1109\/TEVC.2019.2896967","volume":"23","author":"Z Ma","year":"2019","unstructured":"Ma, Z., Wang, Y.: Evolutionary constrained multiobjective optimization: test suite construction and performance comparisons. IEEE Trans. Evol. Comput. 23(6), 972\u2013986 (2019)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"11_CR25","doi-asserted-by":"publisher","DOI":"10.1016\/j.swevo.2022.101146","volume":"75","author":"MM Mamun","year":"2022","unstructured":"Mamun, M.M., Singh, H.K., Ray, T.: An approach for computationally expensive multi-objective optimization problems with independently evaluable objectives. Swarm Evol. Compt. 75, 101146 (2022)","journal-title":"Swarm Evol. Compt."},{"key":"11_CR26","unstructured":"Montgomery, D.C.: Design and Analysis of Experiments. Wiley, 8th edn. (2012)"},{"key":"11_CR27","doi-asserted-by":"crossref","unstructured":"Rahi, K., Singh, H., Ray, T.: Towards solving expensive optimization problems with heterogeneous constraint costs. In: Proceedings of the Genetic and Evolutionary Computation Conference Companion, pp. 2032\u20132040 (2024)","DOI":"10.1145\/3638530.3664105"},{"key":"11_CR28","doi-asserted-by":"crossref","unstructured":"Rahi, K.H., Singh, H.K., Ray, T.: Investigating the use of sequencing and infeasibility driven strategies for constrained optimization. In: 2019 IEEE Congress on Evolutionary Computation (CEC), pp. 1642\u20131649. IEEE (2019)","DOI":"10.1109\/CEC.2019.8790239"},{"issue":"6","key":"11_CR29","doi-asserted-by":"publisher","first-page":"1103","DOI":"10.1109\/TEVC.2021.3078486","volume":"25","author":"KH Rahi","year":"2021","unstructured":"Rahi, K.H., Singh, H.K., Ray, T.: Partial evaluation strategies for expensive evolutionary constrained optimization. IEEE Trans. Evol. Comput. 25(6), 1103\u20131117 (2021)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"11_CR30","doi-asserted-by":"crossref","unstructured":"Santoshkumar, B., Deb, K.: Surrogate-assisted multi-objective optimization for handling objectives with heterogeneous evaluation times: unconstrained problems. In: 2024 IEEE Congress on Evolutionary Computation (CEC), pp.\u00a01\u20138. IEEE (2024)","DOI":"10.1109\/CEC60901.2024.10612003"},{"key":"11_CR31","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2020.106078","volume":"89","author":"R Tanabe","year":"2020","unstructured":"Tanabe, R., Ishibuchi, H.: An easy-to-use real-world multi-objective optimization problem suite. Appl. Soft Comput. 89, 106078 (2020)","journal-title":"Appl. Soft Comput."},{"issue":"6","key":"11_CR32","doi-asserted-by":"publisher","first-page":"712","DOI":"10.1109\/TEVC.2007.892759","volume":"11","author":"Q Zhang","year":"2007","unstructured":"Zhang, Q., Li, H.: MOEA\/D: a multiobjective evolutionary algorithm based on decomposition. IEEE Trans. Evol. Comput. 11(6), 712\u2013731 (2007)","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"3","key":"11_CR33","doi-asserted-by":"publisher","first-page":"456","DOI":"10.1109\/TEVC.2009.2033671","volume":"4","author":"Q Zhang","year":"2010","unstructured":"Zhang, Q., Liu, W., Tsang, E., Virginas, B.: Expensive multi-objective optimization by MOEA\/D with gaussian process model. IEEE Trans. Evol. Comput. 4(3), 456\u2013474 (2010)","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"2","key":"11_CR34","doi-asserted-by":"publisher","first-page":"125","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. J. 8(2), 125\u2013148 (2000)","journal-title":"Evol. Comput. J."}],"container-title":["Lecture Notes in Computer Science","Evolutionary Multi-Criterion Optimization"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-96-3538-2_11","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,28]],"date-time":"2025-02-28T12:58:14Z","timestamp":1740747494000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-96-3538-2_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9789819635375","9789819635382"],"references-count":34,"URL":"https:\/\/doi.org\/10.1007\/978-981-96-3538-2_11","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"28 February 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"EMO","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Evolutionary Multi-Criterion Optimization","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Canberra, ACT","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Australia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 March 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 March 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"emo2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.emo2025.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}