{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T09:34:30Z","timestamp":1743154470404,"version":"3.40.3"},"publisher-location":"Cham","reference-count":47,"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_1","type":"book-chapter","created":{"date-parts":[[2024,9,6]],"date-time":"2024-09-06T23:02:54Z","timestamp":1725663774000},"page":"3-19","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Selection Strategy Based on\u00a0Proper Pareto Optimality in\u00a0Evolutionary Multi-objective Optimization"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-5025-2361","authenticated-orcid":false,"given":"Kai","family":"Li","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0001-0283-3378","authenticated-orcid":false,"given":"Kangnian","family":"Lin","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0004-0932-2847","authenticated-orcid":false,"given":"Ruihao","family":"Zheng","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1152-6780","authenticated-orcid":false,"given":"Zhenkun","family":"Wang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,9,7]]},"reference":[{"issue":"1","key":"1_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":"1_CR2","doi-asserted-by":"crossref","unstructured":"Batista, L.S., Campelo, F., Guimar\u00e3es, F.G., Ram\u00edrez, J.A.: A comparison of dominance criteria in many-objective optimization problems. In: 2011 IEEE Congress of Evolutionary Computation (CEC), pp. 2359\u20132366. IEEE (2011)","DOI":"10.1109\/CEC.2011.5949909"},{"key":"1_CR3","unstructured":"Bellman, R.: Dynamic Programming, vol. 1, pp. 3\u201325. Princeton University Press, Princeton, NJ, USA (1958)"},{"key":"1_CR4","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1007\/s10710-005-6164-x","volume":"6","author":"CAC Coello","year":"2005","unstructured":"Coello, C.A.C., Cort\u00e9s, N.C.: Solving multiobjective optimization problems using an artificial immune system. Genet. Program Evolvable Mach. 6, 163\u2013190 (2005)","journal-title":"Genet. Program Evolvable Mach."},{"key":"1_CR5","first-page":"30","volume":"26","author":"K Deb","year":"1996","unstructured":"Deb, K., Goyal, M., et al.: A combined genetic adaptive search (GeneAS) for engineering design. Comput. Sci. Inf. 26, 30\u201345 (1996)","journal-title":"Comput. Sci. Inf."},{"issue":"4","key":"1_CR6","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":"1_CR7","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"222","DOI":"10.1007\/3-540-36970-8_16","volume-title":"Evolutionary Multi-Criterion Optimization","author":"K Deb","year":"2003","unstructured":"Deb, K., Mohan, M., Mishra, S.: Towards a quick computation of well-spread Pareto-optimal solutions. In: Fonseca, C.M., Fleming, P.J., Zitzler, E., Thiele, L., Deb, K. (eds.) EMO 2003. LNCS, vol. 2632, pp. 222\u2013236. Springer, Heidelberg (2003). https:\/\/doi.org\/10.1007\/3-540-36970-8_16"},{"issue":"2","key":"1_CR8","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."},{"key":"1_CR9","doi-asserted-by":"crossref","unstructured":"Deb, K., do\u00a0Val\u00a0Lopes, C.L., Martins, F.V.C., Wanner, E.F.: Identifying Pareto fronts reliably using a multi-stage reference-vector-based framework. IEEE Trans. Evol. Comput. 28(1), 252\u2013266 (2024)","DOI":"10.1109\/TEVC.2023.3246922"},{"issue":"1","key":"1_CR10","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1109\/TEVC.2006.876362","volume":"11","author":"F Di Pierro","year":"2007","unstructured":"Di Pierro, F., Khu, S.T., Savic, D.A.: An investigation on preference order ranking scheme for multiobjective evolutionary optimization. IEEE Trans. Evol. Comput. 11(1), 17\u201345 (2007)","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"8","key":"1_CR11","doi-asserted-by":"publisher","first-page":"8300","DOI":"10.1109\/TCYB.2021.3049635","volume":"52","author":"J Duan","year":"2021","unstructured":"Duan, J., He, Z., Yen, G.G.: Robust multiobjective optimization for vehicle routing problem with time windows. IEEE Trans. Cybern. 52(8), 8300\u20138314 (2021)","journal-title":"IEEE Trans. Cybern."},{"key":"1_CR12","doi-asserted-by":"publisher","first-page":"62","DOI":"10.1007\/978-3-540-31880-4_5","volume-title":"Evolutionary Multi-Criterion Optimization","author":"M Emmerich","year":"2005","unstructured":"Emmerich, M., Beume, N., Naujoks, B.: An EMO algorithm using the hypervolume measure as selection criterion. In: Coello Coello, C.A., Hern\u00e1ndez Aguirre, A., Zitzler, E. (eds.) Evolutionary Multi-Criterion Optimization, pp. 62\u201376. Springer, Berlin, Heidelberg (2005). https:\/\/doi.org\/10.1007\/978-3-540-31880-4_5"},{"issue":"3","key":"1_CR13","doi-asserted-by":"publisher","first-page":"618","DOI":"10.1016\/0022-247X(68)90201-1","volume":"22","author":"AM Geoffrion","year":"1968","unstructured":"Geoffrion, A.M.: Proper efficiency and the theory of vector maximization. J. Math. Anal. Appl. 22(3), 618\u2013630 (1968)","journal-title":"J. Math. Anal. Appl."},{"key":"1_CR14","doi-asserted-by":"publisher","first-page":"338","DOI":"10.1016\/j.ins.2014.08.071","volume":"293","author":"I Giagkiozis","year":"2015","unstructured":"Giagkiozis, I., Fleming, P.J.: Methods for multi-objective optimization: an analysis. Inf. Sci. 293, 338\u2013350 (2015)","journal-title":"Inf. Sci."},{"key":"1_CR15","doi-asserted-by":"publisher","first-page":"428","DOI":"10.1007\/978-3-642-37140-0_33","volume-title":"Evolutionary Multi-Criterion Optimization","author":"I Giagkiozis","year":"2013","unstructured":"Giagkiozis, I., Purshouse, R.C., Fleming, P.J.: Generalized decomposition. In: Purshouse, R.C., Fleming, P.J., Fonseca, C.M., Greco, S., Shaw, J. (eds.) Evolutionary Multi-Criterion Optimization, pp. 428\u2013442. Springer, Berlin, Heidelberg (2013). https:\/\/doi.org\/10.1007\/978-3-642-37140-0_33"},{"key":"1_CR16","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"814","DOI":"10.1007\/978-3-319-45823-6_76","volume-title":"Parallel Problem Solving from Nature \u2013 PPSN XIV","author":"AP Guerreiro","year":"2016","unstructured":"Guerreiro, A.P., Fonseca, C.M.: Hypervolume sharpe-ratio indicator: formalization and first theoretical results. In: Handl, J., Hart, E., Lewis, P.R., L\u00f3pez-Ib\u00e1\u00f1ez, M., Ochoa, G., Paechter, B. (eds.) PPSN 2016. LNCS, vol. 9921, pp. 814\u2013823. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-45823-6_76"},{"key":"1_CR17","doi-asserted-by":"publisher","DOI":"10.1007\/978-0-387-84858-7","volume-title":"The Elements of Statistical Learning","author":"T Hastie","year":"2009","unstructured":"Hastie, T., Tibshirani, R., Friedman, J.: The Elements of Statistical Learning. Springer, New York, NY (2009). https:\/\/doi.org\/10.1007\/978-0-387-84858-7"},{"key":"1_CR18","doi-asserted-by":"crossref","unstructured":"Ikeda, K., Kita, H., Kobayashi, S.: Failure of Pareto-based MOEAs: does non-dominated really mean near to optimal? In: Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No. 01TH8546), vol.\u00a02, pp. 957\u2013962. IEEE (2001)","DOI":"10.1109\/CEC.2001.934293"},{"key":"1_CR19","doi-asserted-by":"publisher","first-page":"231","DOI":"10.1007\/978-3-642-44973-4_24","volume-title":"Learning and Intelligent Optimization","author":"H Ishibuchi","year":"2013","unstructured":"Ishibuchi, H., Akedo, N., Nojima, Y.: A study on the specification of a scalarizing function in MOEA\/D for many-objective knapsack problems. In: Nicosia, G., Pardalos, P. (eds.) Learning and Intelligent Optimization, pp. 231\u2013246. Springer, Berlin, Heidelberg (2013). https:\/\/doi.org\/10.1007\/978-3-642-44973-4_24"},{"issue":"2","key":"1_CR20","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1109\/TEVC.2016.2587749","volume":"21","author":"H Ishibuchi","year":"2016","unstructured":"Ishibuchi, H., Setoguchi, Y., Masuda, H., Nojima, Y.: Performance of decomposition-based many-objective algorithms strongly depends on Pareto front shapes. IEEE Trans. Evol. Comput. 21(2), 169\u2013190 (2016)","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"10","key":"1_CR21","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. Inf. Sci. 34(10), 8807\u20138824 (2022)","journal-title":"J. King Saud Univ. Comput. Inf. Sci."},{"issue":"4","key":"1_CR22","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":"5","key":"1_CR23","doi-asserted-by":"publisher","first-page":"694","DOI":"10.1109\/TEVC.2014.2373386","volume":"19","author":"K Li","year":"2014","unstructured":"Li, K., Deb, K., Zhang, Q., Kwong, S.: An evolutionary many-objective optimization algorithm based on dominance and decomposition. IEEE Trans. Evol. Comput. 19(5), 694\u2013716 (2014)","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"3","key":"1_CR24","doi-asserted-by":"publisher","first-page":"1417","DOI":"10.1109\/TCYB.2019.2918087","volume":"51","author":"Z Liang","year":"2019","unstructured":"Liang, Z., Hu, K., Ma, X., Zhu, Z.: A many-objective evolutionary algorithm based on a two-round selection strategy. IEEE Trans. Cybern. 51(3), 1417\u20131429 (2019)","journal-title":"IEEE Trans. Cybern."},{"key":"1_CR25","doi-asserted-by":"crossref","unstructured":"Liu, H.l., Li, X.: The multiobjective evolutionary algorithm based on determined weight and sub-regional search. In: 2009 IEEE Congress on Evolutionary Computation (CEC), pp. 1928\u20131934. IEEE (2009)","DOI":"10.1109\/CEC.2009.4983176"},{"key":"1_CR26","doi-asserted-by":"publisher","first-page":"101069","DOI":"10.1016\/j.swevo.2022.101069","volume":"71","author":"Y Liu","year":"2022","unstructured":"Liu, Y., Liu, J., Teng, X.: Single-particle optimization for network embedding preserving both local and global information. Swarm Evol. Comput. 71, 101069 (2022)","journal-title":"Swarm Evol. Comput."},{"key":"1_CR27","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1016\/j.ins.2022.11.047","volume":"620","author":"Y Liu","year":"2023","unstructured":"Liu, Y., Liu, J., Wu, K.: Cost-effective competition on social networks: a multi-objective optimization perspective. Inf. Sci. 620, 31\u201346 (2023)","journal-title":"Inf. Sci."},{"issue":"11","key":"1_CR28","doi-asserted-by":"publisher","first-page":"5585","DOI":"10.1109\/TCYB.2020.2988896","volume":"51","author":"Y Liu","year":"2020","unstructured":"Liu, Y., Zhu, N., Li, M.: Solving many-objective optimization problems by a Pareto-based evolutionary algorithm with preprocessing and a penalty mechanism. IEEE Trans. Cybern. 51(11), 5585\u20135594 (2020)","journal-title":"IEEE Trans. Cybern."},{"key":"1_CR29","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"151","DOI":"10.1007\/978-3-642-19893-9_11","volume-title":"Evolutionary Multi-Criterion Optimization","author":"A L\u00f3pez Jaimes","year":"2011","unstructured":"L\u00f3pez Jaimes, A., Coello Coello, C.A., Aguirre, H., Tanaka, K.: Adaptive objective space partitioning using conflict information for many-objective optimization. In: Takahashi, R.H.C., Deb, K., Wanner, E.F., Greco, S. (eds.) EMO 2011. LNCS, vol. 6576, pp. 151\u2013165. Springer, Heidelberg (2011). https:\/\/doi.org\/10.1007\/978-3-642-19893-9_11"},{"key":"1_CR30","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4615-5563-6","volume-title":"Nonlinear Multiobjective Optimization","author":"K Miettinen","year":"2012","unstructured":"Miettinen, K.: Nonlinear Multiobjective Optimization. Springer, Cham (2012). https:\/\/doi.org\/10.1007\/978-1-4615-5563-6"},{"key":"1_CR31","doi-asserted-by":"publisher","first-page":"190240","DOI":"10.1109\/ACCESS.2020.3032240","volume":"8","author":"LM Pang","year":"2020","unstructured":"Pang, L.M., Ishibuchi, H., Shang, K.: NSGA-II with simple modification works well on a wide variety of many-objective problems. IEEE Access 8, 190240\u2013190250 (2020)","journal-title":"IEEE Access"},{"issue":"4","key":"1_CR32","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1109\/MCI.2017.2742868","volume":"12","author":"Y Tian","year":"2017","unstructured":"Tian, Y., Cheng, R., Zhang, X., Jin, Y.: PlatEMO: a MATLAB platform for evolutionary multi-objective optimization [educational forum]. IEEE Comput. Intell. Mag. 12(4), 73\u201387 (2017)","journal-title":"IEEE Comput. Intell. Mag."},{"key":"1_CR33","doi-asserted-by":"publisher","first-page":"111006","DOI":"10.1016\/j.asoc.2023.111006","volume":"149","author":"Z Wang","year":"2023","unstructured":"Wang, Z., Li, Q., Li, G., Zhang, Q.: Multi-objective decomposition evolutionary algorithm with objective modification-based dominance and external archive. Appl. Soft Comput. 149, 111006 (2023)","journal-title":"Appl. Soft Comput."},{"issue":"2","key":"1_CR34","doi-asserted-by":"publisher","first-page":"1117","DOI":"10.1007\/s40747-021-00543-2","volume":"9","author":"Z Wang","year":"2023","unstructured":"Wang, Z., Li, Q., Yang, Q., Ishibuchi, H.: The dilemma between eliminating dominance-resistant solutions and preserving boundary solutions of extremely convex Pareto fronts. Complex Intell. Syst. 9(2), 1117\u20131126 (2023)","journal-title":"Complex Intell. Syst."},{"issue":"2","key":"1_CR35","doi-asserted-by":"publisher","first-page":"217","DOI":"10.1109\/TEVC.2018.2844286","volume":"23","author":"Z Wang","year":"2018","unstructured":"Wang, Z., Ong, Y.S., Ishibuchi, H.: On scalable multiobjective test problems with hardly dominated boundaries. IEEE Trans. Evol. Comput. 23(2), 217\u2013231 (2018)","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"3","key":"1_CR36","doi-asserted-by":"publisher","first-page":"1984","DOI":"10.1109\/TCYB.2023.3312476","volume":"54","author":"Z Wang","year":"2024","unstructured":"Wang, Z., Yao, S., Li, G., Zhang, Q.: Multiobjective combinatorial optimization using a single deep reinforcement learning model. IEEE Trans. Cybern. 54(3), 1984\u20131996 (2024)","journal-title":"IEEE Trans. Cybern."},{"issue":"2","key":"1_CR37","doi-asserted-by":"publisher","first-page":"474","DOI":"10.1109\/TCYB.2015.2403849","volume":"46","author":"Z Wang","year":"2015","unstructured":"Wang, Z., Zhang, Q., Zhou, A., Gong, M., Jiao, L.: Adaptive replacement strategies for MOEA\/D. IEEE Trans. Cybern. 46(2), 474\u2013486 (2015)","journal-title":"IEEE Trans. Cybern."},{"issue":"8","key":"1_CR38","doi-asserted-by":"publisher","first-page":"8326","DOI":"10.1109\/TCYB.2021.3049712","volume":"52","author":"Z Wang","year":"2021","unstructured":"Wang, Z., et al.: Multiobjective optimization-aided decision-making system for large-scale manufacturing planning. IEEE Trans. Cybern. 52(8), 8326\u20138339 (2021)","journal-title":"IEEE Trans. Cybern."},{"key":"1_CR39","doi-asserted-by":"publisher","first-page":"346","DOI":"10.1007\/978-981-99-5844-3_25","volume-title":"International Conference on Neural Computing for Advanced Applications","author":"Z Wei","year":"2023","unstructured":"Wei, Z., Wang, H., Wang, S., Zhang, S., Xiao, D.: Complementary environmental selection for\u00a0evolutionary many-objective optimization. In: Zhang, H., et al. (eds.) International Conference on Neural Computing for Advanced Applications, pp. 346\u2013359. Springer, Singapore (2023). https:\/\/doi.org\/10.1007\/978-981-99-5844-3_25"},{"key":"1_CR40","doi-asserted-by":"publisher","first-page":"101539","DOI":"10.1016\/j.swevo.2024.101539","volume":"86","author":"Z Wei","year":"2024","unstructured":"Wei, Z., et al.: Many-objective evolutionary algorithm based on parallel distance for handling irregular pareto fronts. Swarm Evol. Comput. 86, 101539 (2024)","journal-title":"Swarm Evol. Comput."},{"key":"1_CR41","doi-asserted-by":"crossref","unstructured":"Ye, R., Chen, L., Liao, W., Zhang, J., Ishibuchi, H.: Data-driven preference sampling for pareto front learning. arXiv preprint arXiv:2404.08397 (2024)","DOI":"10.1145\/3638529.3654024"},{"key":"1_CR42","doi-asserted-by":"crossref","unstructured":"Ye, R., Chen, L., Zhang, J., Ishibuchi, H.: Evolutionary preference sampling for pareto set learning. arXiv preprint arXiv:2404.08414 (2024)","DOI":"10.1145\/3638529.3654024"},{"key":"1_CR43","unstructured":"Ye, R., Tang, M.: PraFFL: a preference-aware scheme in fair federated learning. arXiv preprint arXiv:2404.08973 (2024)"},{"issue":"1","key":"1_CR44","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1109\/TEVC.2015.2420112","volume":"20","author":"Y Yuan","year":"2015","unstructured":"Yuan, Y., Xu, H., Wang, B., Yao, X.: A new dominance relation-based evolutionary algorithm for many-objective optimization. IEEE Trans. Evol. Comput. 20(1), 16\u201337 (2015)","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"6","key":"1_CR45","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."},{"key":"1_CR46","doi-asserted-by":"crossref","unstructured":"Zheng, R., Wang, Z.: A generalized scalarization method for evolutionary multi-objective optimization. In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), vol.\u00a037, pp. 12518\u201312525 (2023)","DOI":"10.1609\/aaai.v37i10.26474"},{"issue":"4","key":"1_CR47","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1109\/4235.797969","volume":"3","author":"E Zitzler","year":"1999","unstructured":"Zitzler, E., Thiele, L.: Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach. IEEE Trans. Evol. Comput. 3(4), 257\u2013271 (1999)","journal-title":"IEEE Trans. Evol. Comput."}],"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_1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,6]],"date-time":"2024-09-06T23:13:10Z","timestamp":1725664390000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-70085-9_1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031700842","9783031700859"],"references-count":47,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-70085-9_1","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":"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"}}]}}