{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T04:32:32Z","timestamp":1743136352128,"version":"3.40.3"},"publisher-location":"Cham","reference-count":19,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783031147135"},{"type":"electronic","value":"9783031147142"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-14714-2_15","type":"book-chapter","created":{"date-parts":[[2022,8,13]],"date-time":"2022-08-13T21:03:13Z","timestamp":1660424593000},"page":"207-219","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Evolutionary Approaches to\u00a0Improving the\u00a0Layouts of\u00a0Instance-Spaces"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6555-7721","authenticated-orcid":false,"given":"Kevin","family":"Sim","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5405-4413","authenticated-orcid":false,"given":"Emma","family":"Hart","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,8,14]]},"reference":[{"key":"15_CR1","unstructured":"Deap: Distributed evolutionary algorithms in Python. https:\/\/deap.readthedocs.io\/en\/master\/"},{"key":"15_CR2","unstructured":"Matilda: Melbourne algorithm test instance library with data analytics. https:\/\/matilda.unimelb.edu.au\/matilda\/"},{"key":"15_CR3","unstructured":"Umap: Uniform manifold approximation and projection for dimension reduction. https:\/\/umap-learn.readthedocs.io\/en\/latest\/index.html"},{"issue":"1","key":"15_CR4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1162\/106365603321828970","volume":"11","author":"N Hansen","year":"2003","unstructured":"Hansen, N., M\u00fcller, S.D., Koumoutsakos, P.: Reducing the time complexity of the derandomized evolution strategy with covariance matrix adaptation (CMA-ES). Evol. Comput. 11(1), 1\u201318 (2003)","journal-title":"Evol. Comput."},{"issue":"1","key":"15_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41467-021-24642-3","volume":"12","author":"K Hasselmann","year":"2021","unstructured":"Hasselmann, K., Ligot, A., Ruddick, J., Birattari, M.: Empirical assessment and comparison of neuro-evolutionary methods for the automatic off-line design of robot swarms. Nat. Commun. 12(1), 1\u201311 (2021)","journal-title":"Nat. Commun."},{"key":"15_CR6","doi-asserted-by":"crossref","unstructured":"Le Goff, L.K., et al.: Sample and time efficient policy learning with CMA-ES and Bayesian optimisation. In: Artificial Life Conference Proceedings, pp. 432\u2013440. MIT Press (2020)","DOI":"10.1162\/isal_a_00299"},{"key":"15_CR7","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"114","DOI":"10.1007\/978-3-030-16670-0_8","volume-title":"Genetic Programming","author":"A Lensen","year":"2019","unstructured":"Lensen, A., Xue, B., Zhang, M.: Can genetic programming do manifold learning too? In: Sekanina, L., Hu, T., Louren\u00e7o, N., Richter, H., Garc\u00eda-S\u00e1nchez, P. (eds.) EuroGP 2019. LNCS, vol. 11451, pp. 114\u2013130. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-16670-0_8"},{"key":"15_CR8","doi-asserted-by":"crossref","unstructured":"Lensen, A., Xue, B., Zhang, M.: Genetic programming for manifold learning: preserving local topology. IEEE Trans. Evol. Comput. (2021)","DOI":"10.26686\/wgtn.13058786"},{"key":"15_CR9","unstructured":"Loshchilov, I., Hutter, F.: CMA-ES for hyperparameter optimization of deep neural networks. arXiv preprint arXiv:1604.07269 (2016)"},{"key":"15_CR10","unstructured":"Van der Maaten, L., Hinton, G.: Visualizing data using t-SNE. J. Mach. Learn. Res. 9(11) (2008)"},{"issue":"1","key":"15_CR11","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1007\/s10994-017-5629-5","volume":"107","author":"MA Mu\u00f1oz","year":"2017","unstructured":"Mu\u00f1oz, M.A., Villanova, L., Baatar, D., Smith-Miles, K.: Instance spaces for machine learning classification. Mach. Learn. 107(1), 109\u2013147 (2017). https:\/\/doi.org\/10.1007\/s10994-017-5629-5","journal-title":"Mach. Learn."},{"issue":"3","key":"15_CR12","doi-asserted-by":"publisher","first-page":"203","DOI":"10.3233\/IDA-1998-2304","volume":"2","author":"M Partridge","year":"1998","unstructured":"Partridge, M., Calvo, R.A.: Fast dimensionality reduction and simple PCA. Intell. Data Anal. 2(3), 203\u2013214 (1998)","journal-title":"Intell. Data Anal."},{"key":"15_CR13","doi-asserted-by":"crossref","unstructured":"Schofield, F., Lensen, A.: Using genetic programming to find functional mappings for UMAP embeddings. In: 2021 IEEE Congress on Evolutionary Computation (CEC), pp. 704\u2013711. IEEE (2021)","DOI":"10.1109\/CEC45853.2021.9504848"},{"key":"15_CR14","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1016\/j.cor.2013.11.015","volume":"45","author":"K Smith-Miles","year":"2014","unstructured":"Smith-Miles, K., Baatar, D., Wreford, B., Lewis, R.: Towards objective measures of algorithm performance across instance space. Comput. Oper. Res. 45, 12\u201324 (2014)","journal-title":"Comput. Oper. Res."},{"key":"15_CR15","doi-asserted-by":"publisher","first-page":"102","DOI":"10.1016\/j.cor.2015.04.022","volume":"63","author":"K Smith-Miles","year":"2015","unstructured":"Smith-Miles, K., Bowly, S.: Generating new test instances by evolving in instance space. Comput. Oper. Res. 63, 102\u2013113 (2015)","journal-title":"Comput. Oper. Res."},{"key":"15_CR16","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"266","DOI":"10.1007\/978-3-642-13800-3_29","volume-title":"Learning and Intelligent Optimization","author":"K Smith-Miles","year":"2010","unstructured":"Smith-Miles, K., van Hemert, J., Lim, X.Y.: Understanding TSP difficulty by learning from evolved instances. In: Blum, C., Battiti, R. (eds.) LION 2010. LNCS, vol. 6073, pp. 266\u2013280. Springer, Heidelberg (2010). https:\/\/doi.org\/10.1007\/978-3-642-13800-3_29"},{"key":"15_CR17","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"524","DOI":"10.1007\/978-3-642-25566-3_41","volume-title":"Learning and Intelligent Optimization","author":"K Smith-Miles","year":"2011","unstructured":"Smith-Miles, K., Lopes, L.: Generalising algorithm performance in instance space: a timetabling case study. In: Coello, C.A.C. (ed.) LION 2011. LNCS, vol. 6683, pp. 524\u2013538. Springer, Heidelberg (2011). https:\/\/doi.org\/10.1007\/978-3-642-25566-3_41"},{"issue":"5","key":"15_CR18","doi-asserted-by":"publisher","first-page":"875","DOI":"10.1016\/j.cor.2011.07.006","volume":"39","author":"K Smith-Miles","year":"2012","unstructured":"Smith-Miles, K., Lopes, L.: Measuring instance difficulty for combinatorial optimization problems. Comput. Oper. Res. 39(5), 875\u2013889 (2012)","journal-title":"Comput. Oper. Res."},{"issue":"201","key":"15_CR19","first-page":"1","volume":"22","author":"Y Wang","year":"2021","unstructured":"Wang, Y., Huang, H., Rudin, C., Shaposhnik, Y.: Understanding how dimension reduction tools work: an empirical approach to deciphering t-SNE, UMAP, TriMap, and PaCMAP for data visualization. J. Mach. Learn. Res. 22(201), 1\u201373 (2021)","journal-title":"J. Mach. Learn. Res."}],"container-title":["Lecture Notes in Computer Science","Parallel Problem Solving from Nature \u2013 PPSN XVII"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-14714-2_15","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T16:42:36Z","timestamp":1710261756000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-14714-2_15"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031147135","9783031147142"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-14714-2_15","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"14 August 2022","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":"Dortmund","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Germany","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 September 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 September 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ppsn2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ppsn2022.cs.tu-dortmund.de\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"185","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"85","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"46% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3.75","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3.11","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}