{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T03:21:11Z","timestamp":1743132071355,"version":"3.40.3"},"publisher-location":"Cham","reference-count":26,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031700842"},{"type":"electronic","value":"9783031700859"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[[2024]]},"DOI":"10.1007\/978-3-031-70085-9_12","type":"book-chapter","created":{"date-parts":[[2024,9,6]],"date-time":"2024-09-06T23:02:54Z","timestamp":1725663774000},"page":"186-201","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["An Unbounded Archive-Based Inverse Model in\u00a0Evolutionary Multi-objective Optimization"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7759-1254","authenticated-orcid":false,"given":"Rongguang","family":"Ye","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7087-9909","authenticated-orcid":false,"given":"Longcan","family":"Chen","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6137-2594","authenticated-orcid":false,"given":"Jinyuan","family":"Zhang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9186-6472","authenticated-orcid":false,"given":"Hisao","family":"Ishibuchi","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,9,7]]},"reference":[{"key":"12_CR1","doi-asserted-by":"publisher","unstructured":"Deb, K.: Multi-objective optimisation using evolutionary algorithms: an introduction. In: Wang, L., Ng, A., Deb, K. (eds.) Multi-objective Evolutionary Optimisation for Product Design and Manufacturing. Springer, London (2011). https:\/\/doi.org\/10.1007\/978-0-85729-652-8_1","DOI":"10.1007\/978-0-85729-652-8_1"},{"key":"12_CR2","doi-asserted-by":"crossref","unstructured":"Miettinen, K.: Nonlinear multiobjective optimization, vol. 12. Springer Science & Business Media (1999)","DOI":"10.1007\/978-1-4615-5563-6"},{"key":"12_CR3","doi-asserted-by":"publisher","unstructured":"Deb, K., Thiele, L., Laumanns, M., Zitzler, E.: Scalable test problems for evolutionary multiobjective optimization. In: Abraham, A., Jain, L., Goldberg, R. (eds.) Evolutionary Multiobjective Optimization. Advanced Information and Knowledge Processing. Springer, London (2005). https:\/\/doi.org\/10.1007\/1-84628-137-7_6","DOI":"10.1007\/1-84628-137-7_6"},{"issue":"2","key":"12_CR4","doi-asserted-by":"publisher","first-page":"227","DOI":"10.1162\/evco_a_00269","volume":"28","author":"M Li","year":"2020","unstructured":"Li, M., Yao, X.: What weights work for you? adapting weights for any pareto front shape in decomposition-based evolutionary multiobjective optimisation. Evol. Comput. 28(2), 227\u2013253 (2020)","journal-title":"Evol. Comput."},{"key":"12_CR5","doi-asserted-by":"publisher","first-page":"428","DOI":"10.1007\/s10957-013-0346-0","volume":"162","author":"RS Burachik","year":"2014","unstructured":"Burachik, R.S., Kaya, C.Y., Rizvi, M.M.: A new scalarization technique to approximate pareto fronts of problems with disconnected feasible sets. J. Optimizat. Theory Appli. 162, 428\u2013446 (2014)","journal-title":"J. Optimizat. Theory Appli."},{"issue":"2","key":"12_CR6","doi-asserted-by":"publisher","first-page":"421","DOI":"10.1109\/TCYB.2015.2403131","volume":"46","author":"S Jiang","year":"2015","unstructured":"Jiang, S., Yang, S.: An improved multiobjective optimization evolutionary algorithm based on decomposition for complex pareto fronts. IEEE Trans. Cybernet. 46(2), 421\u2013437 (2015)","journal-title":"IEEE Trans. Cybernet."},{"issue":"3","key":"12_CR7","doi-asserted-by":"publisher","first-page":"1106","DOI":"10.1109\/TCYB.2018.2883914","volume":"50","author":"Y Tian","year":"2018","unstructured":"Tian, Y., Zhang, X., Cheng, R., He, C., Jin, Y.: Guiding evolutionary multiobjective optimization with generic front modeling. IEEE Trans. Cybernet. 50(3), 1106\u20131119 (2018)","journal-title":"IEEE Trans. Cybernet."},{"key":"12_CR8","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"682","DOI":"10.1007\/978-3-319-10762-2_67","volume-title":"Parallel Problem Solving from Nature \u2013 PPSN XIII","author":"S Zapotecas Mart\u00ednez","year":"2014","unstructured":"Zapotecas Mart\u00ednez, S., Sosa Hern\u00e1ndez, V.A., Aguirre, H., Tanaka, K., Coello Coello, C.A.: Using a family of curves to approximate the pareto front of a multi-objective optimization problem. In: Bartz-Beielstein, T., Branke, J., Filipi\u010d, B., Smith, J. (eds.) PPSN 2014. LNCS, vol. 8672, pp. 682\u2013691. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-10762-2_67"},{"key":"12_CR9","doi-asserted-by":"crossref","unstructured":"Suresh, A., Deb, K.: Machine learning based prediction of new pareto-optimal solutions from pseudo-weights. IEEE Trans. Evolutionary Comput. (2023) (Early Access)","DOI":"10.1109\/TEVC.2023.3319494"},{"key":"12_CR10","unstructured":"Li, M., L\u00f3pez-Ib\u00e1\u00f1ez, M., Yao, X.: Multi-objective archiving. IEEE Trans. Evolutionary Comput. (2023) (Early Access)"},{"key":"12_CR11","doi-asserted-by":"crossref","unstructured":"Ishibuchi, H., Pang, L.M., Shang, K.: A new framework of evolutionary multi-objective algorithms with an unbounded external archive, pp. 283\u2013290 (2020)","DOI":"10.36227\/techrxiv.11661276"},{"issue":"6","key":"12_CR12","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":"1","key":"12_CR13","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1504\/IJCSM.2023.133532","volume":"18","author":"X Li","year":"2023","unstructured":"Li, X., Li, K., Zeng, T., Ye, T., Zhang, L., Wang, H.: Artificial bee colony with multiple search strategies and a new updating mechanism. Int. J. Comput. Sci. Math. 18(1), 44\u201353 (2023)","journal-title":"Int. J. Comput. Sci. Math."},{"issue":"4","key":"12_CR14","doi-asserted-by":"publisher","first-page":"387","DOI":"10.1504\/IJCSM.2022.125917","volume":"15","author":"K Li","year":"2022","unstructured":"Li, K., et al.: A new artificial bee colony algorithm based on modified search strategy. Int. J. Comput. Sci. Math. 15(4), 387\u2013395 (2022)","journal-title":"Int. J. Comput. Sci. Math."},{"issue":"10","key":"12_CR15","first-page":"8807","volume":"34","author":"K Li","year":"2022","unstructured":"Li, K., Wang, H., Wang, W., Wang, F., Cui, Z.: Improving artificial bee colony algorithm using modified nearest neighbor sequence. J. King Saud Univ.-Comput. Inform. Sci. 34(10), 8807\u20138824 (2022)","journal-title":"J. King Saud Univ.-Comput. Inform. Sci."},{"issue":"6","key":"12_CR16","doi-asserted-by":"publisher","first-page":"5287","DOI":"10.1007\/s40747-022-00759-w","volume":"8","author":"AA Bidgoli","year":"2022","unstructured":"Bidgoli, A.A., et al.: Machine learning-based framework to cover optimal pareto-front in many-objective optimization. Complex Intell. Syst. 8(6), 5287\u20135308 (2022)","journal-title":"Complex Intell. Syst."},{"issue":"3","key":"12_CR17","doi-asserted-by":"publisher","first-page":"557","DOI":"10.1023\/A:1017536311488","volume":"110","author":"C Hillermeier","year":"2001","unstructured":"Hillermeier, C.: Generalized homotopy approach to multiobjective optimization. J. Optim. Theory Appl. 110(3), 557\u2013583 (2001)","journal-title":"J. Optim. Theory Appl."},{"issue":"5","key":"12_CR18","doi-asserted-by":"publisher","first-page":"1167","DOI":"10.1109\/TEVC.2009.2021467","volume":"13","author":"A Zhou","year":"2009","unstructured":"Zhou, A., Zhang, Q., Jin, Y.: Approximating the set of pareto-optimal solutions in both the decision and objective spaces by an estimation of distribution algorithm. IEEE Trans. Evol. Comput. 13(5), 1167\u20131189 (2009)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"12_CR19","doi-asserted-by":"publisher","DOI":"10.1016\/j.enconman.2020.113543","volume":"226","author":"F Zhu","year":"2020","unstructured":"Zhu, F., et al.: A coordinated optimization framework for long-term complementary operation of a large-scale hydro-photovoltaic hybrid system: Nonlinear modeling, multi-objective optimization and robust decision-making. Energy Convers. Manage. 226, 113543 (2020)","journal-title":"Energy Convers. Manage."},{"key":"12_CR20","doi-asserted-by":"crossref","unstructured":"Van\u00a0Veldhuizen, D.A.: Multiobjective evolutionary algorithms: classifications, analyses, and new innovations. Air Force Institute of Technology (1999)","DOI":"10.1145\/298151.298382"},{"key":"12_CR21","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"688","DOI":"10.1007\/978-3-540-24694-7_71","volume-title":"MICAI 2004: Advances in Artificial Intelligence","author":"CA Coello Coello","year":"2004","unstructured":"Coello Coello, C.A., Reyes Sierra, M.: A study of the parallelization of a coevolutionary multi-objective evolutionary algorithm. In: Monroy, R., Arroyo-Figueroa, G., Sucar, L.E., Sossa, H. (eds.) MICAI 2004. LNCS (LNAI), vol. 2972, pp. 688\u2013697. Springer, Heidelberg (2004). https:\/\/doi.org\/10.1007\/978-3-540-24694-7_71"},{"key":"12_CR22","doi-asserted-by":"crossref","unstructured":"Fonseca, C.M., Paquete, L., L\u00f3pez-Ib\u00e1nez, M.: An improved dimension-sweep algorithm for the hypervolume indicator. In: Proceedings of IEEE International Conference on Evolutionary Computation, pp. 1157\u20131163. IEEE (2006)","DOI":"10.1109\/CEC.2006.1688440"},{"issue":"2","key":"12_CR23","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."},{"issue":"4","key":"12_CR24","doi-asserted-by":"publisher","first-page":"577","DOI":"10.1109\/TEVC.2013.2281535","volume":"18","author":"K Deb","year":"2013","unstructured":"Deb, K., Jain, H.: An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, part i: Solving problems with box constraints. IEEE Trans. Evol. Comput. 18(4), 577\u2013601 (2013)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"12_CR25","doi-asserted-by":"publisher","first-page":"89497","DOI":"10.1109\/ACCESS.2020.2990567","volume":"8","author":"J Blank","year":"2020","unstructured":"Blank, J., Deb, K.: Pymoo: multi-objective optimization in python. IEEE Access 8, 89497\u201389509 (2020)","journal-title":"IEEE Access"},{"key":"12_CR26","unstructured":"Paszke, A., et\u00a0al.: Pytorch: An imperative style, high-performance deep learning library, vol. 32 (2019)"}],"container-title":["Lecture Notes in Computer Science","Parallel Problem Solving from Nature \u2013 PPSN XVIII"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-70085-9_12","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,27]],"date-time":"2024-11-27T21:39:52Z","timestamp":1732743592000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-70085-9_12"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031700842","9783031700859"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-70085-9_12","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"7 September 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors declare that they have no conflict of interest.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interest"}},{"value":"PPSN","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Parallel Problem Solving from Nature","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Hagenberg","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Austria","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 September 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 September 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ppsn2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ppsn2024.fh-ooe.at\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}