{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,7]],"date-time":"2025-10-07T14:31:51Z","timestamp":1759847511829,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":37,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,6,25]],"date-time":"2020-06-25T00:00:00Z","timestamp":1593043200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100012230","name":"Guangdong Science and Technology Department","doi-asserted-by":"publisher","award":["2017ZT07X386,2020B121201001,2019A1515110177"],"award-info":[{"award-number":["2017ZT07X386,2020B121201001,2019A1515110177"]}],"id":[{"id":"10.13039\/501100012230","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005304","name":"Agence Nationale de la Recherche","doi-asserted-by":"publisher","award":["ANR-11-LABX-0056-LMH"],"award-info":[{"award-number":["ANR-11-LABX-0056-LMH"]}],"id":[{"id":"10.13039\/501100005304","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100010226","name":"Department of Education of Guangdong Province","doi-asserted-by":"publisher","award":["2017KSYS008"],"award-info":[{"award-number":["2017KSYS008"]}],"id":[{"id":"10.13039\/501100010226","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Science, Technology and Innovation Commission of Shenzhen Municipality","award":["KQTD2016112514355531"],"award-info":[{"award-number":["KQTD2016112514355531"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,6,25]]},"DOI":"10.1145\/3377930.3390163","type":"proceedings-article","created":{"date-parts":[[2020,6,29]],"date-time":"2020-06-29T19:29:12Z","timestamp":1593458952000},"page":"805-813","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":18,"title":["From understanding genetic drift to a smart-restart parameter-less compact genetic algorithm"],"prefix":"10.1145","author":[{"given":"Benjamin","family":"Doerr","sequence":"first","affiliation":[{"name":"Institut Polytechnique de Paris, Palaiseau, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weijie","family":"Zheng","sequence":"additional","affiliation":[{"name":"Southern University of Science and Technology, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2020,6,26]]},"reference":[{"doi-asserted-by":"publisher","key":"e_1_3_2_1_1_1","DOI":"10.1145\/3205455.3205627"},{"key":"e_1_3_2_1_2_1","volume-title":"PPSN","author":"B\u00f6ttcher S\u00fcntje","year":"2010","unstructured":"S\u00fcntje B\u00f6ttcher , Benjamin Doerr , and Frank Neumann . 2010 . Optimal fixed and adaptive mutation rates for the LeadingOnes problem. In Parallel Problem Solving from Nature , PPSN 2010. Springer, 1--10. S\u00fcntje B\u00f6ttcher, Benjamin Doerr, and Frank Neumann. 2010. Optimal fixed and adaptive mutation rates for the LeadingOnes problem. In Parallel Problem Solving from Nature, PPSN 2010. Springer, 1--10."},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_3_1","DOI":"10.1145\/2739480.2754814"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_4_1","DOI":"10.1016\/j.tcs.2018.09.024"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_5_1","DOI":"10.1145\/3299904.3340304"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_6_1","DOI":"10.1145\/3321707.3321747"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_7_1","DOI":"10.1145\/3377930.3389823"},{"volume-title":"Theory of Evolutionary Computation: Recent Developments in Discrete Optimization","author":"Doerr Benjamin","unstructured":"Benjamin Doerr and Carola Doerr . 2020. Theory of parameter control for discrete black-box optimization: provable performance gains through dynamic parameter choices . In Theory of Evolutionary Computation: Recent Developments in Discrete Optimization , Benjamin Doerr and Frank Neumann (Eds.). Springer , 271--321. Also available at https:\/\/arxiv.org\/abs\/1804.05650. Benjamin Doerr and Carola Doerr. 2020. Theory of parameter control for discrete black-box optimization: provable performance gains through dynamic parameter choices. In Theory of Evolutionary Computation: Recent Developments in Discrete Optimization, Benjamin Doerr and Frank Neumann (Eds.). Springer, 271--321. Also available at https:\/\/arxiv.org\/abs\/1804.05650.","key":"e_1_3_2_1_8_1"},{"key":"e_1_3_2_1_9_1","volume-title":"A simplified run time analysis of the univariate marginal distribution algorithm on LeadingOnes. CoRR abs\/2004.04978","author":"Doerr Benjamin","year":"2020","unstructured":"Benjamin Doerr and Martin Krejca . 2020. A simplified run time analysis of the univariate marginal distribution algorithm on LeadingOnes. CoRR abs\/2004.04978 ( 2020 ). arXiv:2004.04978 Benjamin Doerr and Martin Krejca. 2020. A simplified run time analysis of the univariate marginal distribution algorithm on LeadingOnes. CoRR abs\/2004.04978 (2020). arXiv:2004.04978"},{"key":"e_1_3_2_1_10_1","volume-title":"Genetic and Evolutionary Computation Conference, GECCO","author":"Doerr Benjamin","year":"2020","unstructured":"Benjamin Doerr and Martin S. Krejca . 2020. Bivariate estimation-of-distribution algorithms can find an exponential number of optima . In Genetic and Evolutionary Computation Conference, GECCO 2020 . ACM. To appear. Benjamin Doerr and Martin S. Krejca. 2020. Bivariate estimation-of-distribution algorithms can find an exponential number of optima. In Genetic and Evolutionary Computation Conference, GECCO 2020. ACM. To appear."},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_11_1","DOI":"10.1109\/TEVC.2019.2956633"},{"key":"e_1_3_2_1_12_1","volume-title":"Krejca","author":"Doerr Benjamin","year":"2020","unstructured":"Benjamin Doerr and Martin S . Krejca . 2020 . The univariate marginal distribution algorithm copes well with deception and epistasis. In Evolutionary Computation in Combinatorial Optimization, EvoCOP 2020. Springer , 51--66. Benjamin Doerr and Martin S. Krejca. 2020. The univariate marginal distribution algorithm copes well with deception and epistasis. In Evolutionary Computation in Combinatorial Optimization, EvoCOP 2020. Springer, 51--66."},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_13_1","DOI":"10.1016\/j.tcs.2014.03.015"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_14_1","DOI":"10.1145\/3071178.3071301"},{"key":"e_1_3_2_1_15_1","volume-title":"From understanding genetic drift to a smart-restart parameter-less compact genetic algorithm. CoRR abs\/2004.07141","author":"Doerr Benjamin","year":"2020","unstructured":"Benjamin Doerr and Weijie Zheng . 2020. From understanding genetic drift to a smart-restart parameter-less compact genetic algorithm. CoRR abs\/2004.07141 ( 2020 ). arXiv:2004.07141 Benjamin Doerr and Weijie Zheng. 2020. From understanding genetic drift to a smart-restart parameter-less compact genetic algorithm. CoRR abs\/2004.07141 (2020). arXiv:2004.07141"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_16_1","DOI":"10.1109\/TEVC.2020.2987361"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_17_1","DOI":"10.1007\/s11047-006-9001-0"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_18_1","DOI":"10.1016\/S0304-3975(01)00182-7"},{"key":"e_1_3_2_1_19_1","volume-title":"Genetic and Evolutionary Computation Conference, GECCO","author":"Friedrich Tobias","year":"2016","unstructured":"Tobias Friedrich , Timo K\u00f6tzing , and Martin S. Krejca . 2016. EDAs cannot be balanced and stable . In Genetic and Evolutionary Computation Conference, GECCO 2016 . ACM, 1139--1146. Tobias Friedrich, Timo K\u00f6tzing, and Martin S. Krejca. 2016. EDAs cannot be balanced and stable. In Genetic and Evolutionary Computation Conference, GECCO 2016. ACM, 1139--1146."},{"key":"e_1_3_2_1_20_1","volume-title":"Genetic and Evolutionary Computation Conference, GECCO","author":"Brian","year":"2014","unstructured":"Brian W. Goldman and William F. Punch. 2014. Parameter-less population pyramid . In Genetic and Evolutionary Computation Conference, GECCO 2014 . ACM, 785--792. Brian W. Goldman and William F. Punch. 2014. Parameter-less population pyramid. In Genetic and Evolutionary Computation Conference, GECCO 2014. ACM, 785--792."},{"key":"e_1_3_2_1_21_1","volume-title":"Genetic and Evolutionary Computation Conference, GECCO","author":"Georges","year":"1999","unstructured":"Georges R. Harik and Fernando G. Lobo. 1999. A parameter-less genetic algorithm . In Genetic and Evolutionary Computation Conference, GECCO 1999 . 258--265. Georges R. Harik and Fernando G. Lobo. 1999. A parameter-less genetic algorithm. In Genetic and Evolutionary Computation Conference, GECCO 1999. 258--265."},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_22_1","DOI":"10.1109\/4235.797971"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_23_1","DOI":"10.1145\/3205455.3205608"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_24_1","DOI":"10.1162\/106365605774666921"},{"volume-title":"Theory of Evolutionary Computation: Recent Developments in Discrete Optimization","author":"Krejca Martin","unstructured":"Martin Krejca and Carsten Witt . 2020. Theory of estimation-of-distribution algorithms . In Theory of Evolutionary Computation: Recent Developments in Discrete Optimization , Benjamin Doerr and Frank Neumann (Eds.). Springer , 405--442. Also available at https:\/\/arxiv.org\/abs\/1806.05392. Martin Krejca and Carsten Witt. 2020. Theory of estimation-of-distribution algorithms. In Theory of Evolutionary Computation: Recent Developments in Discrete Optimization, Benjamin Doerr and Frank Neumann (Eds.). Springer, 405--442. Also available at https:\/\/arxiv.org\/abs\/1806.05392.","key":"e_1_3_2_1_25_1"},{"doi-asserted-by":"crossref","unstructured":"Pedro Larra\u00f1aga and Jos\u00e9 Antonio Lozano (Eds.). 2002. Estimation of Distribution Algorithms. Springer.  Pedro Larra\u00f1aga and Jos\u00e9 Antonio Lozano (Eds.). 2002. Estimation of Distribution Algorithms. Springer.","key":"e_1_3_2_1_26_1","DOI":"10.1007\/978-1-4615-1539-5"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_27_1","DOI":"10.1145\/3299904.3340316"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_28_1","DOI":"10.1145\/3205455.3205576"},{"key":"e_1_3_2_1_29_1","volume-title":"Genetic and Evolutionary Computation Conference, GECCO","author":"Cl\u00e1udio","year":"2004","unstructured":"Cl\u00e1udio F. Lima and Fernando G. Lobo. 2004. Parameter-less optimization with the extended compact genetic algorithm and iterated local search . In Genetic and Evolutionary Computation Conference, GECCO 2004 . Springer, 1328--1339. Cl\u00e1udio F. Lima and Fernando G. Lobo. 2004. Parameter-less optimization with the extended compact genetic algorithm and iterated local search. In Genetic and Evolutionary Computation Conference, GECCO 2004. Springer, 1328--1339."},{"key":"e_1_3_2_1_30_1","volume-title":"PPSN","author":"M\u00fchlenbein Heinz","year":"1992","unstructured":"Heinz M\u00fchlenbein . 1992 . How genetic algorithms really work: mutation and hillclimbing. In Parallel Problem Solving from Nature , PPSN 1992. Elsevier, 15--26. Heinz M\u00fchlenbein. 1992. How genetic algorithms really work: mutation and hillclimbing. In Parallel Problem Solving from Nature, PPSN 1992. Elsevier, 15--26."},{"key":"e_1_3_2_1_31_1","volume-title":"PPSN","author":"M\u00fchlenbein Heinz","year":"1996","unstructured":"Heinz M\u00fchlenbein and Gerhard Paass . 1996 . From recombination of genes to the estimation of distributions I. Binary parameters. In Parallel Problem Solving from Nature , PPSN 1996. Springer, 178--187. Heinz M\u00fchlenbein and Gerhard Paass. 1996. From recombination of genes to the estimation of distributions I. Binary parameters. In Parallel Problem Solving from Nature, PPSN 1996. Springer, 178--187."},{"key":"e_1_3_2_1_32_1","volume-title":"Lobo","author":"Pelikan Martin","year":"2015","unstructured":"Martin Pelikan , Mark Hauschild , and Fernando G . Lobo . 2015 . Estimation of distribution algorithms. In Springer Handbook of Computational Intelligence, Janusz Kacprzyk and Witold Pedrycz (Eds.). Springer , 899--928. Martin Pelikan, Mark Hauschild, and Fernando G. Lobo. 2015. Estimation of distribution algorithms. In Springer Handbook of Computational Intelligence, Janusz Kacprzyk and Witold Pedrycz (Eds.). Springer, 899--928."},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_33_1","DOI":"10.1007\/978-3-540-24855-2_3"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_34_1","DOI":"10.1109\/TEVC.2012.2202241"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_35_1","DOI":"10.1007\/s00453-018-0480-z"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_36_1","DOI":"10.1162\/106365606776022751"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_37_1","DOI":"10.1109\/TEVC.2003.820663"}],"event":{"sponsor":["SIGEVO ACM Special Interest Group on Genetic and Evolutionary Computation"],"acronym":"GECCO '20","name":"GECCO '20: Genetic and Evolutionary Computation Conference","location":"Canc\u00fan Mexico"},"container-title":["Proceedings of the 2020 Genetic and Evolutionary Computation Conference"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3377930.3390163","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3377930.3390163","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T22:41:07Z","timestamp":1750200067000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3377930.3390163"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,6,25]]},"references-count":37,"alternative-id":["10.1145\/3377930.3390163","10.1145\/3377930"],"URL":"https:\/\/doi.org\/10.1145\/3377930.3390163","relation":{},"subject":[],"published":{"date-parts":[[2020,6,25]]},"assertion":[{"value":"2020-06-26","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}