{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,23]],"date-time":"2025-04-23T04:17:53Z","timestamp":1745381873129,"version":"3.40.4"},"publisher-location":"Cham","reference-count":31,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031900617","type":"print"},{"value":"9783031900624","type":"electronic"}],"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\/978-3-031-90062-4_33","type":"book-chapter","created":{"date-parts":[[2025,4,22]],"date-time":"2025-04-22T17:24:16Z","timestamp":1745342656000},"page":"527-542","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Using Local Correlation Between Objectives to\u00a0Detect Problem Modality"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6495-006X","authenticated-orcid":false,"given":"Tea","family":"Tu\u0161ar","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0006-6849-4088","authenticated-orcid":false,"given":"Jordan N.","family":"Cork","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,4,17]]},"reference":[{"key":"33_CR1","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1007\/978-3-642-44973-4_4","volume-title":"Learning and Intelligent Optimization","author":"T Abell","year":"2013","unstructured":"Abell, T., Malitsky, Y., Tierney, K.: Features for exploiting black-box optimization problem structure. In: Nicosia, G., Pardalos, P. (eds.) LION 2013. LNCS, vol. 7997, pp. 30\u201336. Springer, Heidelberg (2013). https:\/\/doi.org\/10.1007\/978-3-642-44973-4_4"},{"key":"33_CR2","doi-asserted-by":"publisher","unstructured":"Adair, J., Ochoa, G., Malan, K.M.: Local optima networks for continuous fitness landscapes. In: Companion Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2019). pp. 1407\u20131414. Association for Computing Machinery, New York, NY, USA (2019). https:\/\/doi.org\/10.1145\/3319619.3326852","DOI":"10.1145\/3319619.3326852"},{"issue":"9","key":"33_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.4230\/DAGREP.13.9.1","volume":"13","author":"R Allmendinger","year":"2023","unstructured":"Allmendinger, R., Fonseca, C.M., Sayin, S., Wiecek, M.M., Stiglmayr, M.: Multiobjective optimization on a budget (Dagstuhl Seminar 23361). Dagstuhl Reports 13(9), 1\u201368 (2023). https:\/\/doi.org\/10.4230\/DAGREP.13.9.1","journal-title":"Dagstuhl Reports"},{"issue":"2","key":"33_CR4","doi-asserted-by":"publisher","first-page":"165","DOI":"10.1162\/EVCO_A_00298","volume":"30","author":"D Brockhoff","year":"2022","unstructured":"Brockhoff, D., Auger, A., Hansen, N., Tu\u0161ar, T.: Using well-understood single-objective functions in multiobjective black-box optimization test suites. Evol. Comput. 30(2), 165\u2013193 (2022). https:\/\/doi.org\/10.1162\/EVCO_A_00298","journal-title":"Evol. Comput."},{"key":"33_CR5","doi-asserted-by":"publisher","unstructured":"Chugh, T., Gaspar-Cunha, A., Deutz, A.H., Duro, J.A., Oara, D.C., Rahat, A.: Identifying correlations in understanding and solving many-objective optimisation problems, pp. 241\u2013267. Springer International Publishing, Cham (2023). https:\/\/doi.org\/10.1007\/978-3-031-25263-1_9","DOI":"10.1007\/978-3-031-25263-1_9"},{"key":"33_CR6","doi-asserted-by":"publisher","unstructured":"Fieldsend, J.E., Chugh, T., Allmendinger, R., Miettinen, K.: A feature rich distance-based many-objective visualisable test problem generator. In: Proceedigs of the Genetic and Evolutionary Computation Conference (GECCO 2019). pp. 541\u2013549. Association for Computing Machinery, New York, NY, USA (2019). https:\/\/doi.org\/10.1145\/3321707.3321727","DOI":"10.1145\/3321707.3321727"},{"key":"33_CR7","doi-asserted-by":"crossref","unstructured":"Fonseca, C.M.: Multiobjective genetic algorithms with application to control engineering problems. Ph.D. thesis, University of Sheffield (1995)","DOI":"10.1049\/cp:19951023"},{"issue":"1","key":"33_CR8","doi-asserted-by":"publisher","first-page":"114","DOI":"10.1080\/10556788.2020.1808977","volume":"36","author":"N Hansen","year":"2021","unstructured":"Hansen, N., Auger, A., Ros, R., Mersmann, O., Tu\u0161ar, T., Brockhoff, D.: COCO: a platform for comparing continuous optimizers in a black-box setting. Optim. Methods Softw. 36(1), 114\u2013144 (2021). https:\/\/doi.org\/10.1080\/10556788.2020.1808977","journal-title":"Optim. Methods Softw."},{"key":"33_CR9","doi-asserted-by":"publisher","unstructured":"Jones, T., Forrest, S.: Fitness distance correlation as a measure of problem difficulty for genetic algorithms. In: Proceedings of the International Conference on Genetic Algorithms (ICGA 1995), pp. 184\u2013192. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA (1995). https:\/\/doi.org\/10.5555\/645514.657929","DOI":"10.5555\/645514.657929"},{"key":"33_CR10","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"329","DOI":"10.1007\/978-3-319-54157-0_23","volume-title":"Evolutionary Multi-Criterion Optimization","author":"P Kerschke","year":"2017","unstructured":"Kerschke, P., Grimme, C.: An expedition to multimodal multi-objective optimization landscapes. In: Trautmann, H., et al. (eds.) EMO 2017. LNCS, vol. 10173, pp. 329\u2013343. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-54157-0_23"},{"key":"33_CR11","doi-asserted-by":"publisher","unstructured":"Kerschke, P., Preuss, M.: Exploratory landscape analysis. In: Companion Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 209), pp. 1137\u20131155. Association for Computing Machinery, New York, NY, USA (2019). https:\/\/doi.org\/10.1145\/3319619.3323389","DOI":"10.1145\/3319619.3323389"},{"key":"33_CR12","doi-asserted-by":"publisher","unstructured":"Kerschke, P., et al.: Cell mapping techniques for exploratory landscape analysis. In: Tantar, A.A., et al. (eds.) EVOLVE \u2013 A Bridge between Probability, Set Oriented Numerics, and Evolutionary Computation V. Advances in Intelligent Systems and Computing, vol.\u00a0288, pp. 115\u2013131. Springer International Publishing, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-07494-8_9","DOI":"10.1007\/978-3-319-07494-8_9"},{"key":"33_CR13","doi-asserted-by":"publisher","unstructured":"Kerschke, P., Preuss, M., Wessing, S., Trautmann, H.: Detecting funnel structures by means of exploratory landscape analysis. In: Proceedings of the Conference on Genetic and Evolutionary Computation (GECCO 2015), pp. 265\u2013272. Association for Computing Machinery, New York, NY, USA (2015). https:\/\/doi.org\/10.1145\/2739480.2754642","DOI":"10.1145\/2739480.2754642"},{"key":"33_CR14","doi-asserted-by":"publisher","unstructured":"Kerschke, P., Trautmann, H.: Comprehensive feature-based landscape analysis of continuous and constrained optimization problems using the R-package flacco, pp. 93\u2013123. Springer International Publishing, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-25147-5_7","DOI":"10.1007\/978-3-030-25147-5_7"},{"key":"33_CR15","doi-asserted-by":"publisher","unstructured":"Liang, Z., Cui, Z., Li, M.: Pareto landscape: visualising the landscape of multi-objective optimisation problems. In: Affenzeller, M., et al. (eds.) Parallel Problem Solving from Nature (PPSN XVIII), pp. 299\u2013315. Springer Nature Switzerland, Cham (2024). https:\/\/doi.org\/10.1007\/978-3-031-70085-9_19","DOI":"10.1007\/978-3-031-70085-9_19"},{"key":"33_CR16","unstructured":"Liefooghe, A.: Landscape features for MO-ICOPs. https:\/\/gitlab.com\/aliefooghe\/landscape-features-mo-icops (2024). https:\/\/gitlab.com\/aliefooghe\/landscape-features-mo-icops, gitLab repository"},{"key":"33_CR17","doi-asserted-by":"publisher","unstructured":"Liefooghe, A., Verel, S., Lacroix, B., Z\u0103voianu, A.C., McCall, J.: Landscape features and automated algorithm selection for multi-objective interpolated continuous optimisation problems. In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2021), pp. 421\u2013429. Association for Computing Machinery, New York, NY, USA (2021). https:\/\/doi.org\/10.1145\/3449639.3459353","DOI":"10.1145\/3449639.3459353"},{"issue":"2","key":"33_CR18","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1109\/TIT.1982.1056489","volume":"28","author":"SP Lloyd","year":"1982","unstructured":"Lloyd, S.P.: Least squares quantization in PCM. IEEE Trans. Inf. Theory 28(2), 129\u2013137 (1982). https:\/\/doi.org\/10.1109\/TIT.1982.1056489","journal-title":"IEEE Trans. Inf. Theory"},{"key":"33_CR19","doi-asserted-by":"publisher","unstructured":"Lunacek, M., Whitley, D.: The dispersion metric and the CMA evolution strategy. In: Proceedings of the Conference on Genetic and Evolutionary Computation (GECCO 2006), pp. 477\u2013484. Association for Computing Machinery, New York, NY, USA (2006). https:\/\/doi.org\/10.1145\/1143997.1144085","DOI":"10.1145\/1143997.1144085"},{"key":"33_CR20","doi-asserted-by":"publisher","unstructured":"Malan, K.M., Oberholzer, J.F., Engelbrecht, A.P.: Characterising constrained continuous optimisation problems. In: Proceedings of the Congress on Evolutionary Computation (CEC 2015), pp. 1351\u20131358. IEEE (2015). https:\/\/doi.org\/10.1109\/CEC.2015.7257045","DOI":"10.1109\/CEC.2015.7257045"},{"issue":"1","key":"33_CR21","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1080\/00401706.2000.10485979","volume":"42","author":"MD McKay","year":"1979","unstructured":"McKay, M.D., Beckman, R.J., Conover, W.J.: A comparison of three methods for selecting values of input variables in the analysis of output from a computer code. Technometrics 42(1), 55\u201361 (1979)","journal-title":"Technometrics"},{"key":"33_CR22","doi-asserted-by":"publisher","unstructured":"Mersmann, O., Bischl, B., Trautmann, H., Preuss, M., Weihs, C., Rudolph, G.: Exploratory landscape analysis. In: Proceedings of the Conference on Genetic and Evolutionary Computation (GECCO 2011), pp. 829\u2013836. Association for Computing Machinery, New York, NY, USA (2011). https:\/\/doi.org\/10.1145\/2001576.2001690","DOI":"10.1145\/2001576.2001690"},{"issue":"7","key":"33_CR23","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1007\/s00500-015-1878-z","volume":"21","author":"R Morgan","year":"2015","unstructured":"Morgan, R., Gallagher, M.: Analysing and characterising optimization problems using length scale. Soft. Comput. 21(7), 1735\u20131752 (2015). https:\/\/doi.org\/10.1007\/s00500-015-1878-z","journal-title":"Soft. Comput."},{"key":"33_CR24","doi-asserted-by":"publisher","unstructured":"M\u00fcller, C.L., Sbalzarini, I.F.: Global characterization of the CEC 2005 fitness landscapes using fitness-distance analysis. In: Di\u00a0Chio, C., et al. (eds.) Applications of Evolutionary Computation. Lecture Notes in Computer Science, vol.\u00a06624, pp. 294\u2013303. Springer, Berlin, Heidelberg (2011). https:\/\/doi.org\/10.1007\/978-3-642-20525-5_30","DOI":"10.1007\/978-3-642-20525-5_30"},{"issue":"1","key":"33_CR25","doi-asserted-by":"publisher","first-page":"74","DOI":"10.1109\/TEVC.2014.2302006","volume":"19","author":"MA Mu\u00f1oz","year":"2015","unstructured":"Mu\u00f1oz, M.A., Kirley, M., Halgamuge, S.K.: Exploratory landscape analysis of continuous space optimization problems using information content. IEEE Trans. Evol. Comput. 19(1), 74\u201387 (2015). https:\/\/doi.org\/10.1109\/TEVC.2014.2302006","journal-title":"IEEE Trans. Evol. Comput."},{"key":"33_CR26","unstructured":"Pedregosa, F., et al.: Scikit-learn: machine learning in Python. J. Mach. Learn. Res. 12, 2825\u20132830 (2011). http:\/\/jmlr.org\/papers\/v12\/pedregosa11a.html"},{"key":"33_CR27","doi-asserted-by":"crossref","unstructured":"Prager, R.P.: Pflacco: feature-based landscape analysis of continuous and constrained optimization problems (2024). https:\/\/github.com\/Reiyan\/pflacco. Accessed 15 Nov 2024","DOI":"10.1162\/evco_a_00341"},{"key":"33_CR28","doi-asserted-by":"publisher","unstructured":"Prager, R.P., Trautmann, H.: Pflacco: feature-based landscape analysis of continuous and constrained optimization problems in Python. Evol. Comput., 1\u201325 (2023). https:\/\/doi.org\/10.1162\/evco_a_00341","DOI":"10.1162\/evco_a_00341"},{"key":"33_CR29","doi-asserted-by":"publisher","unstructured":"Rodgers, J.L., Nicewander, W.A.: Thirteen ways to look at the correlation coefficient. Am. Stat. 42(1), 59\u201366 (1988). https:\/\/doi.org\/10.1080\/00031305.1988.10475524","DOI":"10.1080\/00031305.1988.10475524"},{"key":"33_CR30","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"154","DOI":"10.1007\/978-3-030-58115-2_11","volume-title":"Parallel Problem Solving from Nature \u2013 PPSN XVI","author":"L Sch\u00e4permeier","year":"2020","unstructured":"Sch\u00e4permeier, L., Grimme, C., Kerschke, P.: One PLOT to show them all: visualization of efficient sets in multi-objective landscapes. In: B\u00e4ck, T., et al. (eds.) PPSN 2020. LNCS, vol. 12270, pp. 154\u2013167. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58115-2_11"},{"key":"33_CR31","unstructured":"Wessing, S.: Two-stage methods for multimodal optimization. Ph.D. thesis, Technische Universit\u00e4t Dortmund, Fakult\u00e4t f\u00fcr Informatik, Dortmund, Germany (2015). http:\/\/dx.doi.org\/10.17877\/DE290R-7804"}],"container-title":["Lecture Notes in Computer Science","Applications of Evolutionary Computation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-90062-4_33","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,22]],"date-time":"2025-04-22T17:24:20Z","timestamp":1745342660000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-90062-4_33"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031900617","9783031900624"],"references-count":31,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-90062-4_33","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"17 April 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors have no competing interests to declare that\u00a0are relevant to the content of this article.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"EvoApplications","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on the Applications of Evolutionary Computation (Part of EvoStar)","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Trieste","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","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":"23 April 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 April 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"evoapplications2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.evostar.org\/2025\/evoapps\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}