{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,8]],"date-time":"2025-07-08T16:43:56Z","timestamp":1751993036571,"version":"3.40.3"},"publisher-location":"Cham","reference-count":52,"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_8","type":"book-chapter","created":{"date-parts":[[2024,9,6]],"date-time":"2024-09-06T23:02:54Z","timestamp":1725663774000},"page":"117-134","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Evolutionary Multi-objective Diversity Optimization"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3850-1671","authenticated-orcid":false,"given":"Anh Viet","family":"Do","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3478-9201","authenticated-orcid":false,"given":"Mingyu","family":"Guo","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0036-4782","authenticated-orcid":false,"given":"Aneta","family":"Neumann","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2721-3618","authenticated-orcid":false,"given":"Frank","family":"Neumann","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,9,7]]},"reference":[{"key":"8_CR1","doi-asserted-by":"publisher","unstructured":"Alexander, B., Kortman, J., Neumann, A.: Evolution of artistic image variants through feature based diversity optimisation. In: GECCO, pp. 171\u2013178. ACM, New York (2017). https:\/\/doi.org\/10.1145\/3071178.3071342","DOI":"10.1145\/3071178.3071342"},{"key":"8_CR2","doi-asserted-by":"publisher","unstructured":"Arrighi, E., Fernau, H., Lokshtanov, D., de\u00a0Oliveira\u00a0Oliveira, M., Wolf, P.: Diversity in kemeny rank aggregation: A parameterized approach. In: IJCAI, pp. 10\u201316. International Joint Conferences on Artificial Intelligence Organization (Aug 2021). https:\/\/doi.org\/10.24963\/ijcai.2021\/2","DOI":"10.24963\/ijcai.2021\/2"},{"issue":"2","key":"8_CR3","doi-asserted-by":"publisher","first-page":"397","DOI":"10.1016\/j.ejor.2020.11.016","volume":"292","author":"C Audet","year":"2021","unstructured":"Audet, C., Bigeon, J., Cartier, D., Digabel, S.L., Salomon, L.: Performance indicators in multiobjective optimization. Eur. J. Oper. Res. 292(2), 397\u2013422 (2021). https:\/\/doi.org\/10.1016\/j.ejor.2020.11.016","journal-title":"Eur. J. Oper. Res."},{"key":"8_CR4","doi-asserted-by":"publisher","DOI":"10.1016\/j.artint.2021.103644","volume":"303","author":"J Baste","year":"2022","unstructured":"Baste, J., et al.: Diversity of solutions: an exploration through the lens of fixed-parameter tractability theory. Artif. Intell. 303, 103644 (2022). https:\/\/doi.org\/10.1016\/j.artint.2021.103644","journal-title":"Artif. Intell."},{"key":"8_CR5","doi-asserted-by":"publisher","unstructured":"Bossek, J., Kerschke, P., Neumann, A., Wagner, M., Neumann, F., Trautmann, H.: Evolving diverse TSP instances by means of novel and creative mutation operators. In: FOGA 2019. pp. 58\u201371. ACM Press, New York (2019).https:\/\/doi.org\/10.1145\/3299904.3340307","DOI":"10.1145\/3299904.3340307"},{"key":"8_CR6","doi-asserted-by":"publisher","unstructured":"Bossek, J., Neumann, A., Neumann, F.: Breeding diverse packings for the knapsack problem by means of diversity-tailored evolutionary algorithms. In: GECCO, pp. 556\u2013564. ACM, New York (Jun 2021).https:\/\/doi.org\/10.1145\/3449639.3459364","DOI":"10.1145\/3449639.3459364"},{"key":"8_CR7","doi-asserted-by":"publisher","unstructured":"Bossek, J., Neumann, F.: Evolutionary diversity optimization and the minimum spanning tree problem. In: GECCO, pp. 198\u2013206. ACM, New York (Jun 2021).https:\/\/doi.org\/10.1145\/3449639.3459363","DOI":"10.1145\/3449639.3459363"},{"key":"8_CR8","doi-asserted-by":"publisher","unstructured":"Branke, J.: Creating robust solutions by means of evolutionary algorithms, pp. 119-128. Springer, Berlin (1998). https:\/\/doi.org\/10.1007\/bfb0056855","DOI":"10.1007\/bfb0056855"},{"key":"8_CR9","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"280","DOI":"10.1007\/978-3-540-72792-7_22","volume-title":"Integer Programming and Combinatorial Optimization","author":"E Danna","year":"2007","unstructured":"Danna, E., Fenelon, M., Gu, Z., Wunderling, R.: Generating multiple solutions for mixed integer programming problems. In: Fischetti, M., Williamson, D.P. (eds.) IPCO 2007. LNCS, vol. 4513, pp. 280\u2013294. Springer, Heidelberg (2007). https:\/\/doi.org\/10.1007\/978-3-540-72792-7_22"},{"issue":"2","key":"8_CR10","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). https:\/\/doi.org\/10.1109\/4235.996017","journal-title":"IEEE Trans. Evol. Comput."},{"issue":"3","key":"8_CR11","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3561974","volume":"2","author":"A Do","year":"2022","unstructured":"Do, A., Guo, M., Neumann, A., Neumann, F.: Analysis of evolutionary diversity optimization for permutation problems. ACM Trans. Evolutionary Learn. Optimizat. 2(3), 1\u201327 (2022). https:\/\/doi.org\/10.1145\/3561974","journal-title":"ACM Trans. Evolutionary Learn. Optimizat."},{"issue":"10","key":"8_CR12","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). https:\/\/doi.org\/10.1016\/j.advengsoft.2011.05.014","journal-title":"Adv. Eng. Softw."},{"key":"8_CR13","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"342","DOI":"10.1007\/978-3-642-02846-5_29","volume-title":"Logic Programming","author":"T Eiter","year":"2009","unstructured":"Eiter, T., Erdem, E., Erdo\u011fan, H., Fink, M.: Finding similar or diverse solutions in answer set programming. In: Hill, P.M., Warren, D.S. (eds.) ICLP 2009. LNCS, vol. 5649, pp. 342\u2013356. Springer, Heidelberg (2009). https:\/\/doi.org\/10.1007\/978-3-642-02846-5_29"},{"issue":"1","key":"8_CR14","doi-asserted-by":"publisher","first-page":"48","DOI":"10.1016\/0377-2217(90)90297-o","volume":"46","author":"E Erkut","year":"1990","unstructured":"Erkut, E.: The discrete p-dispersion problem. Eur. J. Oper. Res. 46(1), 48\u201360 (1990). https:\/\/doi.org\/10.1016\/0377-2217(90)90297-o","journal-title":"Eur. J. Oper. Res."},{"key":"8_CR15","doi-asserted-by":"publisher","unstructured":"Fomin, F.V., Golovach, P.A., Jaffke, L., Philip, G., Sagunov, D.: Diverse pairs of matchings. In: ISAAC pp. 26:1\u201326:12. Schloss Dagstuhl - Leibniz-Zentrum f\u00fcr Informatik, Dagstuhl, Germany (2020).https:\/\/doi.org\/10.4230\/LIPICS.ISAAC.2020.26","DOI":"10.4230\/LIPICS.ISAAC.2020.26"},{"key":"8_CR16","doi-asserted-by":"publisher","unstructured":"Fomin, F.V., Golovach, P.A., Panolan, F., Philip, G., Saurabh, S.: Diverse collections in matroids and graphs. In: STACS, pp. 31:1\u201331:14. Schloss Dagstuhl - Leibniz-Zentrum f\u00fcr Informatik, Dagstuhl, Germany (2021).https:\/\/doi.org\/10.4230\/LIPICS.STACS.2021.31","DOI":"10.4230\/LIPICS.STACS.2021.31"},{"issue":"1","key":"8_CR17","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1162\/evco_a_00274","volume":"29","author":"W Gao","year":"2021","unstructured":"Gao, W., Nallaperuma, S., Neumann, F.: Feature-based diversity optimization for problem instance classification. Evol. Comput. 29(1), 107\u2013128 (2021). https:\/\/doi.org\/10.1162\/evco_a_00274","journal-title":"Evol. Comput."},{"key":"8_CR18","doi-asserted-by":"publisher","unstructured":"Glover, F., L\u00f8Kketangen, A., Woodruff, D.L.: Scatter search to generate diverse MIP solutions. In: Operations Research\/Computer Science Interfaces Series, pp. 299\u2013317. Springer US, Boston (2000).https:\/\/doi.org\/10.1007\/978-1-4615-4567-5_17","DOI":"10.1007\/978-1-4615-4567-5_17"},{"key":"8_CR19","doi-asserted-by":"crossref","unstructured":"Hanaka, T., Kiyomi, M., Kobayashi, Y., Kobayashi, Y., Kurita, K., Otachi, Y.: A framework to design approximation algorithms for finding diverse solutions in combinatorial problems. In: AAAI 2022, pp. 3758\u20133766. AAAI Press (2022), https:\/\/ojs.aaai.org\/index.php\/AAAI\/article\/view\/20290","DOI":"10.1609\/aaai.v36i4.20290"},{"key":"8_CR20","doi-asserted-by":"publisher","unstructured":"Hanaka, T., Kobayashi, Y., Kurita, K., Lee, S.W., Otachi, Y.: Computing diverse shortest paths efficiently: A theoretical and experimental study. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 36(4), pp. 3758\u20133766 (Jun 2022).https:\/\/doi.org\/10.1609\/aaai.v36i4.20290","DOI":"10.1609\/aaai.v36i4.20290"},{"key":"8_CR21","doi-asserted-by":"publisher","unstructured":"Hanaka, T., Kobayashi, Y., Kurita, K., Otachi, Y.: Finding diverse trees, paths, and more. In: AAAI 2021, vol.\u00a035, pp. 3778\u20133786. AAAI Press (May 2021). https:\/\/doi.org\/10.1609\/aaai.v35i5.16495","DOI":"10.1609\/aaai.v35i5.16495"},{"key":"8_CR22","doi-asserted-by":"publisher","unstructured":"Hao, F., Pei, Z., Yang, L.T.: Diversified top-k maximal clique detection in social internet of things. Future Generat. Comput. Syst. 107, 408\u2013417 (Jun 2020).https:\/\/doi.org\/10.1016\/j.future.2020.02.023","DOI":"10.1016\/j.future.2020.02.023"},{"key":"8_CR23","unstructured":"Hebrard, E., Hnich, B., O\u2019Sullivan, B., Walsh, T.: Finding diverse and similar solutions in constraint programming. In: AAAI, pp. 372\u2013377. AAAI Press \/ The MIT Press (2005)"},{"key":"8_CR24","doi-asserted-by":"publisher","unstructured":"Ingmar, L., de la Banda, M.G., Stuckey, P.J., Tack, G.: Modelling diversity of solutions. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 34(02), pp. 1528\u20131535 (2020). https:\/\/doi.org\/10.1609\/aaai.v34i02.5512","DOI":"10.1609\/aaai.v34i02.5512"},{"key":"8_CR25","doi-asserted-by":"crossref","unstructured":"Johnson, D.J., Trick, M.A.: Cliques, Coloring, and Satisfiability: Second DIMACS Implementation Challenge, Workshop, October 11\u201313, 1993. American Mathematical Society, USA (1996)","DOI":"10.1090\/dimacs\/026"},{"issue":"1","key":"8_CR26","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1162\/evco_a_00242","volume":"27","author":"P Kerschke","year":"2019","unstructured":"Kerschke, P., Hoos, H.H., Neumann, F., Trautmann, H.: Automated algorithm selection: survey and perspectives. Evol. Comput. 27(1), 3\u201345 (2019). https:\/\/doi.org\/10.1162\/evco_a_00242","journal-title":"Evol. Comput."},{"key":"8_CR27","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"287","DOI":"10.1007\/978-3-642-21581-0_23","volume-title":"Theory and Applications of Satisfiability Testing - SAT 2011","author":"A Nadel","year":"2011","unstructured":"Nadel, A.: Generating diverse solutions in SAT. In: Sakallah, K.A., Simon, L. (eds.) SAT 2011. LNCS, vol. 6695, pp. 287\u2013301. Springer, Heidelberg (2011). https:\/\/doi.org\/10.1007\/978-3-642-21581-0_23"},{"key":"8_CR28","doi-asserted-by":"publisher","unstructured":"Neumann, A., Bossek, J., Neumann, F.: Diversifying greedy sampling and evolutionary diversity optimisation for constrained monotone submodular functions. In: GECCO, pp. 261\u2013269. ACM, New York (Jun 2021). https:\/\/doi.org\/10.1145\/3449639.3459385","DOI":"10.1145\/3449639.3459385"},{"key":"8_CR29","doi-asserted-by":"publisher","unstructured":"Neumann, A., Gao, W., Doerr, C., Neumann, F., Wagner, M.: Discrepancy-based evolutionary diversity optimization. In: GECCO, pp. 991\u2013998. ACM, New York (Jul 2018). https:\/\/doi.org\/10.1145\/3205455.3205532","DOI":"10.1145\/3205455.3205532"},{"key":"8_CR30","doi-asserted-by":"publisher","unstructured":"Neumann, A., Gao, W., Wagner, M., Neumann, F.: Evolutionary diversity optimization using multi-objective indicators. In: GECCO, pp. 837\u2013845. ACM, New York (Jul 2019). https:\/\/doi.org\/10.1145\/3321707.3321796","DOI":"10.1145\/3321707.3321796"},{"key":"8_CR31","doi-asserted-by":"publisher","unstructured":"Nikfarjam, A., Bossek, J., Neumann, A., Neumann, F.: Computing diverse sets of high quality TSP tours by EAX-based evolutionary diversity optimisation. In: FOGA 2021. ACM, New York (Sep 2021).https:\/\/doi.org\/10.1145\/3450218.3477310","DOI":"10.1145\/3450218.3477310"},{"key":"8_CR32","doi-asserted-by":"publisher","unstructured":"Nikfarjam, A., Bossek, J., Neumann, A., Neumann, F.: Entropy-based evolutionary diversity optimisation for the traveling salesperson problem. In: GECCO, pp. 600\u2013608. ACM, New York (Jun 2021).https:\/\/doi.org\/10.1145\/3449639.3459384","DOI":"10.1145\/3449639.3459384"},{"key":"8_CR33","doi-asserted-by":"publisher","unstructured":"Parmee, I.C., Bonham, C.R.: Improving Cluster Oriented Genetic Algorithms for High-performance Region Identification, pp. 189-202. Springer, London (2002). https:\/\/doi.org\/10.1007\/978-1-4471-0675-3_16","DOI":"10.1007\/978-1-4471-0675-3_16"},{"key":"8_CR34","doi-asserted-by":"publisher","unstructured":"Pelikan, M., Kalapala, R., Hartmann, A.K.: Hybrid evolutionary algorithms on minimum vertex cover for random graphs. In: GECCO, pp. 547\u2013554. ACM, New York (Jul 2007). https:\/\/doi.org\/10.1145\/1276958.1277073","DOI":"10.1145\/1276958.1277073"},{"key":"8_CR35","unstructured":"Petit, T., Trapp, A.C.: Finding diverse solutions of high quality to constraint optimization problems. In: IJCAI 2015, pp. 260\u2014266. AAAI Press (2015)"},{"key":"8_CR36","doi-asserted-by":"publisher","unstructured":"Pierrot, T., Richard, G., Beguir, K., Cully, A.: Multi-objective quality diversity optimization. In: Proceedings of the Genetic and Evolutionary Computation Conference, GECCO 2022, ACM (Jul 2022). https:\/\/doi.org\/10.1145\/3512290.3528823","DOI":"10.1145\/3512290.3528823"},{"key":"8_CR37","doi-asserted-by":"publisher","unstructured":"Ronald, S.: Finding multiple solutions with an evolutionary algorithm. In: Proceedings of 1995 IEEE International Conference on Evolutionary Computation, vol.\u00a02, pp. 641\u2013646. IEEE (1995). https:\/\/doi.org\/10.1109\/icec.1995.487459","DOI":"10.1109\/icec.1995.487459"},{"key":"8_CR38","doi-asserted-by":"crossref","unstructured":"Rossi, R.A., Ahmed, N.K.: The network data repository with interactive graph analytics and visualization. In: AAAI (2015). https:\/\/networkrepository.com","DOI":"10.1609\/aaai.v29i1.9277"},{"key":"8_CR39","doi-asserted-by":"publisher","unstructured":"Ruffini, M., Vucinic, J., de\u00a0Givry, S., Katsirelos, G., Barbe, S., Schiex, T.: Guaranteed diversity & quality for the weighted CSP. In: ICTAI, pp. 18\u201325. IEEE (Nov 2019). https:\/\/doi.org\/10.1109\/ictai.2019.00012","DOI":"10.1109\/ictai.2019.00012"},{"issue":"5","key":"8_CR40","doi-asserted-by":"publisher","first-page":"1058","DOI":"10.1287\/opre.1080.0633","volume":"57","author":"P Schittekat","year":"2009","unstructured":"Schittekat, P., S\u00f6rensen, K.: Supporting 3pl decisions in the automotive industry by generating diverse solutions to a large-scale location-routing problem. Oper. Res. 57(5), 1058\u20131067 (2009)","journal-title":"Oper. Res."},{"issue":"11","key":"8_CR41","doi-asserted-by":"publisher","first-page":"1300","DOI":"10.1080\/0740817x.2015.1019161","volume":"47","author":"AC Trapp","year":"2015","unstructured":"Trapp, A.C., Konrad, R.A.: Finding diverse optima and near-optima to binary integer programs. IIE Trans. 47(11), 1300\u20131312 (2015). https:\/\/doi.org\/10.1080\/0740817x.2015.1019161","journal-title":"IIE Trans."},{"issue":"3","key":"8_CR42","doi-asserted-by":"publisher","first-page":"201","DOI":"10.1109\/4235.661550","volume":"1","author":"S Tsutsui","year":"1997","unstructured":"Tsutsui, S., Ghosh, A.: Genetic algorithms with a robust solution searching scheme. IEEE Trans. Evol. Comput. 1(3), 201\u2013208 (1997). https:\/\/doi.org\/10.1109\/4235.661550","journal-title":"IEEE Trans. Evol. Comput."},{"key":"8_CR43","doi-asserted-by":"publisher","unstructured":"Ulrich, T., Bader, J., Zitzler, E.: Integrating decision space diversity into hypervolume-based multiobjective search. In: GECCO, pp. 455\u2013462. ACM Press, New York (2010).https:\/\/doi.org\/10.1145\/1830483.1830569","DOI":"10.1145\/1830483.1830569"},{"key":"8_CR44","doi-asserted-by":"publisher","unstructured":"Ulrich, T., Thiele, L.: Maximizing population diversity in single-objective optimization. In: GECCO, pp. 641\u2013648. ACM Press, New York (2011).https:\/\/doi.org\/10.1145\/2001576.2001665","DOI":"10.1145\/2001576.2001665"},{"issue":"6","key":"8_CR45","doi-asserted-by":"publisher","first-page":"281","DOI":"10.1016\/0020-0190(88)90174-3","volume":"28","author":"D Wang","year":"1988","unstructured":"Wang, D., Kuo, Y.S.: A study on two geometric location problems. Inf. Process. Lett. 28(6), 281\u2013286 (1988). https:\/\/doi.org\/10.1016\/0020-0190(88)90174-3","journal-title":"Inf. Process. Lett."},{"key":"8_CR46","doi-asserted-by":"publisher","unstructured":"Wang, J., Cheng, J., Fu, A.W.C.: Redundancy-aware maximal cliques. In: Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2013, pp. 122\u2013130. ACM (Aug 2013). https:\/\/doi.org\/10.1145\/2487575.2487689","DOI":"10.1145\/2487575.2487689"},{"key":"8_CR47","doi-asserted-by":"publisher","unstructured":"Wang, R.J., Xue, K., Shang, H., Qian, C., Fu, H., Fu, Q.: Multi-objective optimization-based selection for quality-diversity by non-surrounded-dominated sorting. In: Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence. IJCAI-2023, International Joint Conferences on Artificial Intelligence Organization (Aug 2023). https:\/\/doi.org\/10.24963\/ijcai.2023\/482","DOI":"10.24963\/ijcai.2023\/482"},{"key":"8_CR48","unstructured":"Ye, Y.: Gset max-cut problem set (2003). https:\/\/web.stanford.edu\/~yyye\/yyye\/Gset\/"},{"issue":"2","key":"8_CR49","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1007\/s00778-015-0408-z","volume":"25","author":"L Yuan","year":"2015","unstructured":"Yuan, L., Qin, L., Lin, X., Chang, L., Zhang, W.: Diversified top-k clique search. VLDB J. 25(2), 171\u2013196 (2015). https:\/\/doi.org\/10.1007\/s00778-015-0408-z","journal-title":"VLDB J."},{"issue":"5","key":"8_CR50","doi-asserted-by":"publisher","first-page":"539","DOI":"10.1080\/03052150410001704863","volume":"36","author":"EM Zechman","year":"2004","unstructured":"Zechman, E.M., Ranjithan, S.R.: An evolutionary algorithm to generate alternatives (EAGA) for engineering optimization problems. Eng. Optim. 36(5), 539\u2013553 (2004). https:\/\/doi.org\/10.1080\/03052150410001704863","journal-title":"Eng. Optim."},{"issue":"2","key":"8_CR51","doi-asserted-by":"publisher","first-page":"156","DOI":"10.1061\/(asce)0733-9496(2007)133:2(156)","volume":"133","author":"EM Zechman","year":"2007","unstructured":"Zechman, E.M., Ranjithan, S.R.: Generating alternatives using evolutionary algorithms for water resources and environmental management problems. J. Water Resour. Plan. Manag. 133(2), 156\u2013165 (2007). https:\/\/doi.org\/10.1061\/(asce)0733-9496(2007)133:2(156)","journal-title":"J. Water Resour. Plan. Manag."},{"key":"8_CR52","doi-asserted-by":"publisher","unstructured":"Zitzler, E., Laumanns, M., Thiele, L.: Spea 2: Improving the strength pareto evolutionary algorithm. Tech. Rep. (2001). https:\/\/doi.org\/10.3929\/ETHZ-A-004284029","DOI":"10.3929\/ETHZ-A-004284029"}],"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_8","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,6]],"date-time":"2024-09-06T23:14:16Z","timestamp":1725664456000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-70085-9_8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031700842","9783031700859"],"references-count":52,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-70085-9_8","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"}}]}}