{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T09:58:34Z","timestamp":1742983114212,"version":"3.40.3"},"publisher-location":"Cham","reference-count":12,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031568510"},{"type":"electronic","value":"9783031568527"}],"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\/978-3-031-56852-7_6","type":"book-chapter","created":{"date-parts":[[2024,3,20]],"date-time":"2024-03-20T20:02:22Z","timestamp":1710964942000},"page":"83-97","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Evolving Staff Training Schedules Using an\u00a0Extensible Fitness Function and\u00a0a\u00a0Domain Specific Language"],"prefix":"10.1007","author":[{"given":"Neil","family":"Urquhart","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kelly","family":"Hunter","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,3,21]]},"reference":[{"doi-asserted-by":"publisher","unstructured":"A tabu search algorithm with controlled randomization for constructing feasible university course timetables. Comput. Oper. Res. 123, 105007 (2020). https:\/\/doi.org\/10.1016\/j.cor.2020.105007","key":"6_CR1","DOI":"10.1016\/j.cor.2020.105007"},{"issue":"2","key":"6_CR2","doi-asserted-by":"publisher","first-page":"673","DOI":"10.1051\/ro\/2021027","volume":"55","author":"M Abdelghany","year":"2021","unstructured":"Abdelghany, M., Yahia, Z., Eltawil, A.B.: A new two-stage variable neighborhood search algorithm for the nurse rostering problem. RAIRO - Oper. Res. 55(2), 673\u2013687 (2021). https:\/\/doi.org\/10.1051\/ro\/2021027","journal-title":"RAIRO - Oper. Res."},{"issue":"3","key":"6_CR3","doi-asserted-by":"publisher","first-page":"411","DOI":"10.1287\/ijoc.1120.0510","volume":"25","author":"EK Burke","year":"2013","unstructured":"Burke, E.K., Curtois, T., Qu, R., Vanden-Berghe, G.: A time predefined variable depth search for nurse rostering. INFORMS J. Comput. 25(3), 411\u2013419 (2013). https:\/\/doi.org\/10.1287\/ijoc.1120.0510","journal-title":"INFORMS J. Comput."},{"key":"6_CR4","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1007\/978-3-319-13749-0_9","volume-title":"Theory and Practice of Natural Computing","author":"E Kent","year":"2014","unstructured":"Kent, E., Atkin, J.A.D., Qu, R.: Vehicle routing in a forestry commissioning operation using ant colony optimisation. In: Dediu, A.-H., Lozano, M., Mart\u00edn-Vide, C. (eds.) TPNC 2014. LNCS, vol. 8890, pp. 95\u2013106. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-13749-0_9"},{"doi-asserted-by":"publisher","unstructured":"Kittel, F., Enenkel, J., Guckert, M., Holznigenkemper, J., Urquhart, N.: Optimisation algorithms for parallel machine scheduling problems with setup times. In: Proceedings of the Genetic and Evolutionary Computation Conference Companion. GECCO \u201921, New York, NY, USA, pp. 131\u2013132. Association for Computing Machinery (2021). https:\/\/doi.org\/10.1145\/3449726.3459487","key":"6_CR5","DOI":"10.1145\/3449726.3459487"},{"key":"6_CR6","series-title":"Advances in Intelligent Systems and Computing","doi-asserted-by":"publisher","first-page":"1456","DOI":"10.1007\/978-3-030-51156-2_169","volume-title":"Intelligent and Fuzzy Techniques: Smart and Innovative Solutions","author":"Y Kondratenko","year":"2021","unstructured":"Kondratenko, Y., Kondratenko, G., Sidenko, I., Taranov, M.: Fuzzy and evolutionary algorithms for transport logistics under uncertainty. In: Kahraman, C., Cevik Onar, S., Oztaysi, B., Sari, I.U., Cebi, S., Tolga, A.C. (eds.) INFUS 2020. AISC, vol. 1197, pp. 1456\u20131463. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-51156-2_169"},{"key":"6_CR7","doi-asserted-by":"publisher","first-page":"56504","DOI":"10.1109\/access.2022.3177280","volume":"10","author":"CM Ngoo","year":"2022","unstructured":"Ngoo, C.M., Goh, S.L., Sze, S.N., Sabar, N.R., Abdullah, S., Kendall, G.: A survey of the nurse rostering solution methodologies: the state-of-the-art and emerging trends. IEEE Access 10, 56504\u201356524 (2022). https:\/\/doi.org\/10.1109\/access.2022.3177280","journal-title":"IEEE Access"},{"unstructured":"Regnell, B., Kuchcinski, K.: A scala embedded DSL for combinatorial optimization in software requirements engineering. In: First Workshop on Domain Specific Languages in Combinatorial Optimization, pp. 19\u201334 (2013)","key":"6_CR8"},{"unstructured":"Service, G.D.: Driver CPC training for qualified drivers (2021). https:\/\/www.gov.uk\/driver-cpc-training","key":"6_CR9"},{"doi-asserted-by":"publisher","unstructured":"Si Ying, P., Mohd-Yusoh, Z.I.: Staff scheduling for a courier distribution centre using evolutionary algorithm. Indonesian J. Electric. Eng. Comput. Sci. 27(2), 1043 (2022). https:\/\/doi.org\/10.11591\/ijeecs.v27.i2.pp1043-1050","key":"6_CR10","DOI":"10.11591\/ijeecs.v27.i2.pp1043-1050"},{"key":"6_CR11","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2020.114268","volume":"170","author":"AW Siddiqui","year":"2021","unstructured":"Siddiqui, A.W., Arshad Raza, S.: A general ontological timetabling-model driven metaheuristics approach based on elite solutions. Expert Syst. Appl. 170, 114268 (2021). https:\/\/doi.org\/10.1016\/j.eswa.2020.114268. https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0957417420309799","journal-title":"Expert Syst. Appl."},{"unstructured":"University, M.: Minizinc constraint modelling language (2020). https:\/\/www.minizinc.org\/","key":"6_CR12"}],"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\/978-3-031-56852-7_6","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,25]],"date-time":"2024-03-25T00:14:31Z","timestamp":1711325671000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-56852-7_6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031568510","9783031568527"],"references-count":12,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-56852-7_6","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":"21 March 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"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":"Aberystwyth","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"United Kingdom","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":"3 March 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 March 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"evoapplications2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.evostar.org\/2024\/evoapps\/","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":"Easy Chair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"77","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":"51","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":"66% - 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":"3.4","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":"1.7","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)"}}]}}