{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T07:28:19Z","timestamp":1769930899845,"version":"3.49.0"},"reference-count":3,"publisher":"MIT Press - Journals","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Evolutionary Computation"],"published-print":{"date-parts":[[2005,12]]},"abstract":"<jats:p> Evolutionary algorithms (EAs) generally come with a large number of parameters that have to be set before the algorithm can be used. Finding appropriate settings is a diffi- cult task. The influence of these parameters on the efficiency of the search performed by an evolutionary algorithm can be very high. But there is still a lack of theoretically justified guidelines to help the practitioner find good values for these parameters. One such parameter is the offspring population size. Using a simplified but still realistic evolutionary algorithm, a thorough analysis of the effects of the offspring population size is presented. The result is a much better understanding of the role of offspring population size in an EA and suggests a simple way to dynamically adapt this parameter when necessary. <\/jats:p>","DOI":"10.1162\/106365605774666921","type":"journal-article","created":{"date-parts":[[2005,11,5]],"date-time":"2005-11-05T22:58:46Z","timestamp":1131231526000},"page":"413-440","source":"Crossref","is-referenced-by-count":189,"title":["On the Choice of the Offspring Population Size in Evolutionary Algorithms"],"prefix":"10.1162","volume":"13","author":[{"given":"Thomas","family":"Jansen","sequence":"first","affiliation":[{"name":"FB Informatik, LS 2, Universit\u00e4t Dortmund, 44221 Dortmund, Germany,"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kenneth A. De","family":"Jong","sequence":"additional","affiliation":[{"name":"Krasnow Institute, George Mason University, Fairfax, VA 22030, USA,"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ingo","family":"Wegener","sequence":"additional","affiliation":[{"name":"FB Informatik, LS 2, Universit\u00e4t Dortmund, 44221 Dortmund, Germany,"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"281","reference":[{"key":"p_7","doi-asserted-by":"publisher","DOI":"10.1016\/S0304-3975(01)00182-7"},{"key":"p_16","doi-asserted-by":"publisher","DOI":"10.1109\/4235.974841"},{"key":"p_19","first-page":"349","author":"Wegener I.","year":"2002","journal-title":"Yao, X., and Mohammadian, M., editors, Evolutionary Optimization, pages"}],"container-title":["Evolutionary Computation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mitpressjournals.org\/doi\/pdf\/10.1162\/106365605774666921","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,3,12]],"date-time":"2021-03-12T21:31:08Z","timestamp":1615584668000},"score":1,"resource":{"primary":{"URL":"https:\/\/direct.mit.edu\/evco\/article\/13\/4\/413-440\/1223"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2005,12]]},"references-count":3,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2005,12]]}},"alternative-id":["10.1162\/106365605774666921"],"URL":"https:\/\/doi.org\/10.1162\/106365605774666921","relation":{},"ISSN":["1063-6560","1530-9304"],"issn-type":[{"value":"1063-6560","type":"print"},{"value":"1530-9304","type":"electronic"}],"subject":[],"published":{"date-parts":[[2005,12]]}}}