{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,30]],"date-time":"2025-03-30T12:10:22Z","timestamp":1743336622668,"version":"3.40.3"},"publisher-location":"Cham","reference-count":18,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031868481","type":"print"},{"value":"9783031868498","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\/978-3-031-86849-8_2","type":"book-chapter","created":{"date-parts":[[2025,3,30]],"date-time":"2025-03-30T11:45:15Z","timestamp":1743335115000},"page":"18-32","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Evolutionary Anytime Algorithms"],"prefix":"10.1007","author":[{"family":"Aishwaryaprajna","sequence":"first","affiliation":[]},{"given":"Jonathan E.","family":"Rowe","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,3,18]]},"reference":[{"key":"2_CR1","doi-asserted-by":"crossref","unstructured":"Bossek, J., Sudholt, D.: Do additional target points speed up evolutionary algorithms? Theor. Comput. Sci. (2023)","DOI":"10.1016\/j.tcs.2023.113757"},{"key":"2_CR2","series-title":"PPSN XI","first-page":"1","volume-title":"Parallel Problem Solving from Nature","author":"S B\u00f6ttcher","year":"2010","unstructured":"B\u00f6ttcher, S., Doerr, B., Neumann, F.: Optimal fixed and adaptive mutation rates for the leadingones problem. In: Schaefer, R., Cotta, C., Ko\u0142odziej, J., Rudolph, G. (eds.) Parallel Problem Solving from Nature. PPSN XI, pp. 1\u201310. Springer, Berlin Heidelberg (2010)"},{"key":"2_CR3","doi-asserted-by":"crossref","unstructured":"Cathabard, S., Lehre, P.K., Yao, X.: Non-uniform mutation rates for problems with unknown solution lengths. In: FOGA 2011: Proceedings of the 11th Workshop Proceedings on Foundations of Genetic Algorithms. ACM (2011)","DOI":"10.1145\/1967654.1967670"},{"key":"2_CR4","unstructured":"Ciesielski, V., Scerri, P.: An anytime algorithm for scheduling of aircraft landing times using genetic algorithms. Aust. J. Intell. Inf. Process. Syst. 206\u2013213 (1997)"},{"key":"2_CR5","unstructured":"Dean, T., Boddy, M.: An analysis of time-dependent planning. In: AAAI 1988: Proceedings of the Seventh National Conference on Artificial Intelligence, pp. 49\u201354 (1988)"},{"key":"2_CR6","doi-asserted-by":"publisher","first-page":"703","DOI":"10.1007\/s00453-018-0477-7","volume":"81","author":"B Doerr","year":"2019","unstructured":"Doerr, B., Doerr, C., K\u00f6tzing, T.: Solving problems with unknown solution length at almost no extra cost. Algorithmica 81, 703\u2013748 (2019)","journal-title":"Algorithmica"},{"key":"2_CR7","series-title":"Natural Computing Series","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/978-3-030-29414-4_1","volume-title":"Theory of Evolutionary Computation","author":"B Doerr","year":"2020","unstructured":"Doerr, B.: Probabilistic tools for the analysis of randomized optimization heuristics. In: Doerr, B., Neumann, F. (eds.) Theory of Evolutionary Computation. NCS, pp. 1\u201387. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-29414-4_1"},{"key":"2_CR8","doi-asserted-by":"crossref","unstructured":"Doerr, B., Jansen, T., Sudholt, D., Winzen, C., Zarges, C.: Optimizing monotone functions can be difficult. In: Parallel Problem Solving from Nature, PPSN XI, pp. 42\u201351 (2010)","DOI":"10.1007\/978-3-642-15844-5_5"},{"issue":"6","key":"2_CR9","doi-asserted-by":"publisher","first-page":"1025","DOI":"10.1109\/TEVC.2019.2956633","volume":"24","author":"B Doerr","year":"2020","unstructured":"Doerr, B., Krejca, M.S.: Significance-based estimation-of-distribution algorithms. IEEE Trans. Evol. Comput. 24(6), 1025\u20131034 (2020)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"2_CR10","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1016\/S0304-3975(01)00182-7","volume":"276","author":"S Droste","year":"2002","unstructured":"Droste, S., Jansen, T., Wegener, I.: On the analysis of the $$(1+1)$$ evolutionary algorithm. Theoret. Comput. Sci. 276, 51\u201381 (2002)","journal-title":"Theoret. Comput. Sci."},{"key":"2_CR11","doi-asserted-by":"crossref","unstructured":"Garnier, J., Kallel, L., Schoenauer, M.: Rigourous hitting times for binary mutations. Evol. Comput. 173\u2013203 (1999)","DOI":"10.1162\/evco.1999.7.2.173"},{"issue":"3","key":"2_CR12","doi-asserted-by":"publisher","first-page":"111","DOI":"10.1016\/j.swevo.2011.08.003","volume":"1","author":"M Hauschild","year":"2011","unstructured":"Hauschild, M., Pelikan, M.: An introduction and survey of estimation of distribution algorithms. Swarm Evol. Comput. 1(3), 111\u2013128 (2011)","journal-title":"Swarm Evol. Comput."},{"key":"2_CR13","doi-asserted-by":"crossref","unstructured":"Jansen, T., Zarges, C.: Fixed budget computations: a different perspective on run time analysis. In: GECCO 2012: Proceedings of the 14th Annual Conference on Genetic and Evolutionary Computation, pp. 1325\u20131332 (2012)","DOI":"10.1145\/2330163.2330347"},{"key":"2_CR14","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1016\/j.tcs.2013.06.007","volume":"545","author":"T Jansen","year":"2014","unstructured":"Jansen, T., Zarges, C.: Performance analysis of randomised search heuristics operating with a fixed budget. Theoret. Comput. Sci. 545, 39\u201358 (2014)","journal-title":"Theoret. Comput. Sci."},{"key":"2_CR15","doi-asserted-by":"crossref","unstructured":"Lehre, P.K., Sudholt, D.: Parallel black-box complexity with tail bounds. IEEE Trans. Evol. Comput. (2019)","DOI":"10.1109\/TEVC.2019.2954234"},{"key":"2_CR16","doi-asserted-by":"crossref","unstructured":"Lengler, J., Steger, A.: Drift analysis and evolutionary algorithms revisited. In: Combinatorics, Probability and Computing, pp. 643\u2013666 (2018)","DOI":"10.1017\/S0963548318000275"},{"key":"2_CR17","doi-asserted-by":"crossref","unstructured":"Rowe, J.E., Aishwaryaprajna. The benefits and limitations of voting mechanisms in evolutionary optimisation. In: Proceedings of the 15th ACM\/SIGEVO Conference on Foundations of Genetic Algorithms, FOGA 2019, pp. 34\u201342. Association for Computing Machinery (2019)","DOI":"10.1145\/3299904.3340305"},{"key":"2_CR18","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1016\/j.tcs.2022.08.014","volume":"940","author":"C Witt","year":"2023","unstructured":"Witt, C.: How majority-vote crossover and estimation-of-distribution algorithms cope with fitness valleys. Theoret. Comput. Sci. 940, 18\u201342 (2023)","journal-title":"Theoret. Comput. Sci."}],"container-title":["Lecture Notes in Computer Science","Evolutionary Computation in Combinatorial Optimization"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-86849-8_2","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,30]],"date-time":"2025-03-30T11:45:31Z","timestamp":1743335131000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-86849-8_2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031868481","9783031868498"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-86849-8_2","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":"18 March 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"EvoCOP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Conference on Evolutionary Computation in Combinatorial Optimization (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":"25","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"evocop2025a","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.evostar.org\/2025\/evocop\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}