{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:19:48Z","timestamp":1750220388898,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":225,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,7,7]],"date-time":"2021-07-07T00:00:00Z","timestamp":1625616000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100000921","name":"European Cooperation in Science and Technology","doi-asserted-by":"publisher","award":["CA15140"],"award-info":[{"award-number":["CA15140"]}],"id":[{"id":"10.13039\/501100000921","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,7,7]]},"DOI":"10.1145\/3449726.3461406","type":"proceedings-article","created":{"date-parts":[[2021,7,8]],"date-time":"2021-07-08T14:50:12Z","timestamp":1625755812000},"page":"369-398","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["A gentle introduction to theory (for non-theoreticians)"],"prefix":"10.1145","author":[{"given":"Benjamin","family":"Doerr","sequence":"first","affiliation":[{"name":"Institut Polytechnique de Paris"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2021,7,8]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/3377930.3390172"},{"key":"e_1_3_2_1_2_1","volume-title":"PPSN 2020","author":"Antipov Denis","year":"2020","unstructured":"[ABD20b] Denis Antipov , Maxim Buzdalov , and Benjamin Doerr . First steps towards a runtime analysis when starting with a good solution. In Parallel Problem Solving From Nature , PPSN 2020 , Part II, pages 560--573. Springer , 2020 . [ABD20b] Denis Antipov, Maxim Buzdalov, and Benjamin Doerr. First steps towards a runtime analysis when starting with a good solution. In Parallel Problem Solving From Nature, PPSN 2020, Part II, pages 560--573. Springer, 2020."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3449639.3459377"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.5555\/1996312"},{"key":"e_1_3_2_1_5_1","volume-title":"PPSN 2020","author":"Antipov Denis","year":"2020","unstructured":"[AD20] Denis Antipov and Benjamin Doerr . Runtime analysis of a heavy-tailed (1 + (\u03bb, \u03bb)) genetic algorithm on jump functions. In Parallel Problem Solving From Nature , PPSN 2020 , Part II, pages 545--559. Springer , 2020 . [AD20] Denis Antipov and Benjamin Doerr. Runtime analysis of a heavy-tailed (1 + (\u03bb, \u03bb)) genetic algorithm on jump functions. In Parallel Problem Solving From Nature, PPSN 2020, Part II, pages 545--559. Springer, 2020."},{"key":"e_1_3_2_1_6_1","first-page":"1459","volume-title":"Genetic and Evolutionary Computation Conference, GECCO 2018","author":"Antipov Denis","year":"2018","unstructured":"[ADFH18] Denis Antipov , Benjamin Doerr , Jiefeng Fang , and Tangi Hetet . Runtime analysis for the (&mu; + \u03bb) EA optimizing OneMax . In Genetic and Evolutionary Computation Conference, GECCO 2018 , pages 1459 -- 1466 . ACM, 2018 . [ADFH18] Denis Antipov, Benjamin Doerr, Jiefeng Fang, and Tangi Hetet. Runtime analysis for the (&mu; + \u03bb) EA optimizing OneMax. In Genetic and Evolutionary Computation Conference, GECCO 2018, pages 1459--1466. ACM, 2018."},{"key":"e_1_3_2_1_7_1","first-page":"169","volume-title":"FOGA 2019","author":"Antipov Denis","year":"2019","unstructured":"[ADK19] Denis Antipov , Benjamin Doerr , and Vitalii Karavaev . A tight runtime analysis for the (1 + (\u03bb, \u03bb)) GA on LeadingOnes. In Foundations of Genetic Algorithms , FOGA 2019 , pages 169 -- 182 . ACM, 2019 . [ADK19] Denis Antipov, Benjamin Doerr, and Vitalii Karavaev. A tight runtime analysis for the (1 + (\u03bb, \u03bb)) GA on LeadingOnes. In Foundations of Genetic Algorithms, FOGA 2019, pages 169--182. ACM, 2019."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/3377930.3390148"},{"key":"e_1_3_2_1_9_1","first-page":"1461","volume-title":"Genetic and Evolutionary Computation Conference, GECCO 2019","author":"Antipov Denis","year":"2019","unstructured":"[ADY19] Denis Antipov , Benjamin Doerr , and Quentin Yang . The efficiency threshold for the offspring population size of the (&mu;, \u03bb) EA . In Genetic and Evolutionary Computation Conference, GECCO 2019 , pages 1461 -- 1469 . ACM, 2019 . [ADY19] Denis Antipov, Benjamin Doerr, and Quentin Yang. The efficiency threshold for the offspring population size of the (&mu;, \u03bb) EA. In Genetic and Evolutionary Computation Conference, GECCO 2019, pages 1461--1469. ACM, 2019."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/CEC.2014.6900602"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tcs.2015.04.008"},{"key":"e_1_3_2_1_12_1","first-page":"2","volume-title":"International Conference on Genetic Algorithms, ICGA 1993","author":"B\u00e4ck Thomas","year":"1993","unstructured":"[B\u00e4c93] Thomas B\u00e4ck . Optimal mutation rates in genetic search . In International Conference on Genetic Algorithms, ICGA 1993 , pages 2 -- 8 . Morgan Kaufmann , 1993 . [B\u00e4c93] Thomas B\u00e4ck. Optimal mutation rates in genetic search. In International Conference on Genetic Algorithms, ICGA 1993, pages 2--8. Morgan Kaufmann, 1993."},{"key":"e_1_3_2_1_13_1","volume-title":"Evolutionary Programming, Genetic Algorithms","author":"B\u00e4ck Thomas","year":"1996","unstructured":"[B\u00e4c96] Thomas B\u00e4ck . Evolutionary Algorithms in Theory and Practice - Evolution Strategies , Evolutionary Programming, Genetic Algorithms . Oxford University Press , 1996 . [B\u00e4c96] Thomas B\u00e4ck. Evolutionary Algorithms in Theory and Practice - Evolution Strategies, Evolutionary Programming, Genetic Algorithms. Oxford University Press, 1996."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/3319619.3322067"},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/3377929.3398148"},{"key":"e_1_3_2_1_16_1","first-page":"59","volume-title":"FOGA 2009","author":"Baswana Surender","year":"2009","unstructured":"[BBD+09] Surender Baswana , Somenath Biswas , Benjamin Doerr , Tobias Friedrich , Piyush P. Kurur , and Frank Neumann . Computing single source shortest paths using single-objective fitness. In Foundations of Genetic Algorithms , FOGA 2009 , pages 59 -- 66 . ACM, 2009 . [BBD+09] Surender Baswana, Somenath Biswas, Benjamin Doerr, Tobias Friedrich, Piyush P. Kurur, and Frank Neumann. Computing single source shortest paths using single-objective fitness. In Foundations of Genetic Algorithms, FOGA 2009, pages 59--66. ACM, 2009."},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3449639.3459367"},{"key":"e_1_3_2_1_18_1","volume-title":"Genetic and Evolutionary Computation Conference, GECCO 2021","author":"Benbaki Riade","year":"2021","unstructured":"[BBD21b] Riade Benbaki , Ziyad Benomar , and Benjamin Doerr . A rigorous runtime analysis of the 2-MMASib on jump functions: ant colony optimizers can cope well with local optima . In Genetic and Evolutionary Computation Conference, GECCO 2021 . ACM, 2021 . To appear. [BBD21b] Riade Benbaki, Ziyad Benomar, and Benjamin Doerr. A rigorous runtime analysis of the 2-MMASib on jump functions: ant colony optimizers can cope well with local optima. In Genetic and Evolutionary Computation Conference, GECCO 2021. ACM, 2021. To appear."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3071178.3071297"},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/3377930.3390184"},{"key":"e_1_3_2_1_21_1","first-page":"1","volume-title":"PPSN 2010","author":"B\u00f6ttcher S\u00fcntje","year":"2010","unstructured":"[BDN10] S\u00fcntje B\u00f6ttcher , Benjamin Doerr , and Frank Neumann . Optimal fixed and adaptive mutation rates for the LeadingOnes problem. In Parallel Problem Solving from Nature , PPSN 2010 , pages 1 -- 10 . Springer , 2010 . [BDN10] S\u00fcntje B\u00f6ttcher, Benjamin Doerr, and Frank Neumann. Optimal fixed and adaptive mutation rates for the LeadingOnes problem. In Parallel Problem Solving from Nature, PPSN 2010, pages 1--10. Springer, 2010."},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1887\/0750308958"},{"key":"e_1_3_2_1_23_1","first-page":"892","volume-title":"PPSN 2014","author":"Badkobeh Golnaz","year":"2014","unstructured":"[BLS14] Golnaz Badkobeh , Per Kristian Lehre , and Dirk Sudholt . Unbiased black-box complexity of parallel search. In Parallel Problem Solving from Nature , PPSN 2014 , pages 892 -- 901 . Springer , 2014 . [BLS14] Golnaz Badkobeh, Per Kristian Lehre, and Dirk Sudholt. Unbiased black-box complexity of parallel search. In Parallel Problem Solving from Nature, PPSN 2014, pages 892--901. Springer, 2014."},{"key":"e_1_3_2_1_24_1","first-page":"102","volume-title":"FOGA 2019","author":"Bossek Jakob","year":"2019","unstructured":"[BS19] Jakob Bossek and Dirk Sudholt . Time complexity analysis of RLS and (1+1) EA for the edge coloring problem. In Foundations of Genetic Algorithms , FOGA 2019 , pages 102 -- 115 . ACM, 2019 . [BS19] Jakob Bossek and Dirk Sudholt. Time complexity analysis of RLS and (1+1) EA for the edge coloring problem. In Foundations of Genetic Algorithms, FOGA 2019, pages 102--115. ACM, 2019."},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2017.2753538"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2020.2985450"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1162\/EVCO_a_00147"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2017.2745715"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00453-020-00743-1"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/3205455.3205591"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/2739480.2754684"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/2739480.2754683"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00453-017-0354-9"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-29414-4_6"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/2463372.2463480"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tcs.2014.11.028"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/2576768.2598341"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.artint.2014.07.009"},{"key":"e_1_3_2_1_39_1","doi-asserted-by":"publisher","DOI":"10.1145\/3071178.3071233"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00453-017-0341-1"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/3321707.3321733"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1145\/3321707.3321731"},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.1145\/2987372"},{"key":"e_1_3_2_1_44_1","first-page":"824","volume-title":"PPSN 2016","author":"Doerr Benjamin","year":"2016","unstructured":"[DDY16] Benjamin Doerr , Carola Doerr , and Jing Yang . k-bit mutation with self-adjusting k outperforms standard bit mutation. In Parallel Problem Solving from Nature , PPSN 2016 , pages 824 -- 834 . Springer , 2016 . [DDY16] Benjamin Doerr, Carola Doerr, and Jing Yang. k-bit mutation with self-adjusting k outperforms standard bit mutation. In Parallel Problem Solving from Nature, PPSN 2016, pages 824--834. Springer, 2016."},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tcs.2019.06.014"},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1145\/2908812.2908956"},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2017.2724201"},{"key":"e_1_3_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00453-018-0502-x"},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1109\/CEC.2007.4424704"},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tcs.2010.10.035"},{"key":"e_1_3_2_1_51_1","doi-asserted-by":"publisher","DOI":"10.1145\/2330163.2330167"},{"key":"e_1_3_2_1_52_1","doi-asserted-by":"publisher","DOI":"10.1162\/evco.2007.15.4.401"},{"key":"e_1_3_2_1_53_1","doi-asserted-by":"publisher","DOI":"10.1145\/1276958.1277192"},{"key":"e_1_3_2_1_54_1","doi-asserted-by":"publisher","DOI":"10.1145\/1830483.1830618"},{"key":"e_1_3_2_1_55_1","first-page":"163","volume-title":"FOGA 2011","author":"Doerr Benjamin","year":"2011","unstructured":"[DJK+11] Benjamin Doerr , Daniel Johannsen , Timo K\u00f6tzing , Per Kristian Lehre , Markus Wagner , and Carola Winzen . Faster black-box algorithms through higher arity operators. In Foundations of Genetic Algorithms , FOGA 2011 , pages 163 -- 172 . ACM, 2011 . [DJK+11] Benjamin Doerr, Daniel Johannsen, Timo K\u00f6tzing, Per Kristian Lehre, Markus Wagner, and Carola Winzen. Faster black-box algorithms through higher arity operators. In Foundations of Genetic Algorithms, FOGA 2011, pages 163--172. ACM, 2011."},{"key":"e_1_3_2_1_56_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tcs.2012.10.059"},{"key":"e_1_3_2_1_57_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00453-016-0187-y"},{"key":"e_1_3_2_1_58_1","doi-asserted-by":"publisher","DOI":"10.1162\/EVCO_a_00055"},{"key":"e_1_3_2_1_59_1","first-page":"13","volume-title":"PPSN 1998","author":"Droste Stefan","year":"1998","unstructured":"[DJW98a] Stefan Droste , Thomas Jansen , and Ingo Wegener . On the optimization of unimodal functions with the (1 + 1) evolutionary algorithm. In Parallel Problem Solving from Nature , PPSN 1998 , pages 13 -- 22 . Springer , 1998 . [DJW98a] Stefan Droste, Thomas Jansen, and Ingo Wegener. On the optimization of unimodal functions with the (1 + 1) evolutionary algorithm. In Parallel Problem Solving from Nature, PPSN 1998, pages 13--22. Springer, 1998."},{"key":"e_1_3_2_1_60_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICEC.1998.700079"},{"key":"e_1_3_2_1_61_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0304-3975(01)00182-7"},{"key":"e_1_3_2_1_62_1","doi-asserted-by":"publisher","DOI":"10.1145\/1830483.1830748"},{"key":"e_1_3_2_1_63_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00453-012-9622-x"},{"key":"e_1_3_2_1_64_1","doi-asserted-by":"publisher","DOI":"10.1145\/2463372.2463565"},{"key":"e_1_3_2_1_65_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tcs.2014.03.015"},{"key":"e_1_3_2_1_66_1","doi-asserted-by":"publisher","DOI":"10.1145\/3321707.3321819"},{"key":"e_1_3_2_1_67_1","doi-asserted-by":"publisher","DOI":"10.1145\/3377930.3390177"},{"key":"e_1_3_2_1_68_1","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2019.2956633"},{"key":"e_1_3_2_1_69_1","first-page":"51","volume-title":"EvoCOP 2020","author":"Doerr Benjamin","year":"2020","unstructured":"[DK20c] Benjamin Doerr and Martin S. Krejca . The univariate marginal distribution algorithm copes well with deception and epistasis. In Evolutionary Computation in Combinatorial Optimization , EvoCOP 2020 , pages 51 -- 66 . Springer , 2020 . [DK20c] Benjamin Doerr and Martin S. Krejca. The univariate marginal distribution algorithm copes well with deception and epistasis. In Evolutionary Computation in Combinatorial Optimization, EvoCOP 2020, pages 51--66. Springer, 2020."},{"key":"e_1_3_2_1_70_1","doi-asserted-by":"publisher","DOI":"10.1145\/3449639.3459352"},{"key":"e_1_3_2_1_71_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tcs.2020.11.028"},{"key":"e_1_3_2_1_72_1","first-page":"245","volume-title":"FOCI 2007","author":"Doerr Benjamin","year":"2007","unstructured":"[DKS07] Benjamin Doerr , Christian Klein , and Tobias Storch . Faster evolutionary algorithms by superior graph representation. In Foundations of Computational Intelligence , FOCI 2007 , pages 245 -- 250 . IEEE, 2007 . [DKS07] Benjamin Doerr, Christian Klein, and Tobias Storch. Faster evolutionary algorithms by superior graph representation. In Foundations of Computational Intelligence, FOCI 2007, pages 245--250. IEEE, 2007."},{"key":"e_1_3_2_1_73_1","doi-asserted-by":"publisher","DOI":"10.1145\/2739480.2754814"},{"key":"e_1_3_2_1_74_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00453-015-0103-x"},{"key":"e_1_3_2_1_75_1","first-page":"803","volume-title":"PPSN 2016","author":"Dang Duc-Cuong","year":"2016","unstructured":"[DL16b] Duc-Cuong Dang and Per Kristian Lehre . Self-adaptation of mutation rates in non-elitist populations. In Parallel Problem Solving from Nature , PPSN 2016 , pages 803 -- 813 . Springer , 2016 . [DL16b] Duc-Cuong Dang and Per Kristian Lehre. Self-adaptation of mutation rates in non-elitist populations. In Parallel Problem Solving from Nature, PPSN 2016, pages 803--813. Springer, 2016."},{"key":"e_1_3_2_1_76_1","doi-asserted-by":"publisher","DOI":"10.1145\/3071178.3071301"},{"key":"e_1_3_2_1_77_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00453-018-0507-5"},{"key":"e_1_3_2_1_78_1","doi-asserted-by":"publisher","DOI":"10.1145\/3205455.3205611"},{"key":"e_1_3_2_1_79_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-29414-4"},{"key":"e_1_3_2_1_80_1","doi-asserted-by":"publisher","DOI":"10.1145\/3205455.3205563"},{"key":"e_1_3_2_1_81_1","doi-asserted-by":"publisher","DOI":"10.1145\/2908812.2908885"},{"key":"e_1_3_2_1_82_1","first-page":"25","volume-title":"FOGA 2019","author":"Doerr Benjamin","year":"2019","unstructured":"[Doe19a] Benjamin Doerr . An exponential lower bound for the runtime of the compact genetic algorithm on jump functions. In Foundations of Genetic Algorithms , FOGA 2019 , pages 25 -- 33 . ACM, 2019 . [Doe19a] Benjamin Doerr. An exponential lower bound for the runtime of the compact genetic algorithm on jump functions. In Foundations of Genetic Algorithms, FOGA 2019, pages 25--33. ACM, 2019."},{"key":"e_1_3_2_1_83_1","doi-asserted-by":"publisher","DOI":"10.1145\/3321707.3321747"},{"key":"e_1_3_2_1_84_1","doi-asserted-by":"publisher","DOI":"10.1145\/3377930.3389823"},{"key":"e_1_3_2_1_85_1","volume-title":"PPSN 2020","author":"Doerr Benjamin","year":"2020","unstructured":"[Doe20b] Benjamin Doerr . Lower bounds for non-elitist evolutionary algorithms via negative multiplicative drift. In Parallel Problem Solving From Nature , PPSN 2020 , Part II, pages 604--618. Springer , 2020 . [Doe20b] Benjamin Doerr. Lower bounds for non-elitist evolutionary algorithms via negative multiplicative drift. In Parallel Problem Solving From Nature, PPSN 2020, Part II, pages 604--618. Springer, 2020."},{"key":"e_1_3_2_1_86_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tcs.2020.09.032"},{"key":"e_1_3_2_1_87_1","doi-asserted-by":"publisher","DOI":"10.1145\/2739480.2754760"},{"key":"e_1_3_2_1_88_1","doi-asserted-by":"publisher","DOI":"10.1109\/CEC.2002.1006209"},{"key":"e_1_3_2_1_89_1","doi-asserted-by":"publisher","DOI":"10.5555\/1761233.1761353"},{"key":"e_1_3_2_1_90_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-24854-5_107"},{"key":"e_1_3_2_1_91_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11047-006-9001-0"},{"key":"e_1_3_2_1_92_1","doi-asserted-by":"publisher","DOI":"10.1145\/3321707.3321837"},{"key":"e_1_3_2_1_93_1","first-page":"48","volume-title":"FOGA 2013","author":"Doerr Benjamin","year":"2013","unstructured":"[DSW13] Benjamin Doerr , Dirk Sudholt , and Carsten Witt . When do evolutionary algorithms optimize separable functions in parallel? In Foundations of Genetic Algorithms , FOGA 2013 , pages 48 -- 59 . ACM, 2013 . [DSW13] Benjamin Doerr, Dirk Sudholt, and Carsten Witt. When do evolutionary algorithms optimize separable functions in parallel? In Foundations of Genetic Algorithms, FOGA 2013, pages 48--59. ACM, 2013."},{"key":"e_1_3_2_1_94_1","doi-asserted-by":"publisher","DOI":"10.1145\/1569901.1569937"},{"key":"e_1_3_2_1_95_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipl.2011.10.004"},{"key":"e_1_3_2_1_96_1","doi-asserted-by":"publisher","DOI":"10.1145\/2330163.2330345"},{"key":"e_1_3_2_1_97_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00453-012-9684-9"},{"key":"e_1_3_2_1_98_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00453-020-00726-2"},{"key":"e_1_3_2_1_99_1","volume-title":"International Joint Conference on Artificial Intelligence, IJCAI 2021","author":"Doerr Benjamin","year":"2021","unstructured":"[DWZ21] Benjamin Doerr , Shouda Wang , and Weijie Zheng . Choosing the right algorithm with hints from complexity theory . In International Joint Conference on Artificial Intelligence, IJCAI 2021 . ijcai.org, 2021 . To appear. [DWZ21] Benjamin Doerr, Shouda Wang, and Weijie Zheng. Choosing the right algorithm with hints from complexity theory. In International Joint Conference on Artificial Intelligence, IJCAI 2021. ijcai.org, 2021. To appear."},{"key":"e_1_3_2_1_100_1","doi-asserted-by":"publisher","DOI":"10.1145\/3377930.3390163"},{"key":"e_1_3_2_1_101_1","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2020.2987361"},{"key":"e_1_3_2_1_102_1","doi-asserted-by":"publisher","DOI":"10.1145\/3449726.3462719"},{"key":"e_1_3_2_1_103_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tcs.2019.05.021"},{"key":"e_1_3_2_1_104_1","doi-asserted-by":"publisher","DOI":"10.1109\/4235.771166"},{"key":"e_1_3_2_1_105_1","volume-title":"Evolutionary algorithms and submodular functions: Benefits of heavy-tailed mutations. CoRR, abs\/1805.10902","author":"Friedrich Tobias","year":"2018","unstructured":"[FGQW18a] Tobias Friedrich , Andreas G\u00f6bel , Francesco Quinzan , and Markus Wagner . Evolutionary algorithms and submodular functions: Benefits of heavy-tailed mutations. CoRR, abs\/1805.10902 , 2018 . [FGQW18a] Tobias Friedrich, Andreas G\u00f6bel, Francesco Quinzan, and Markus Wagner. Evolutionary algorithms and submodular functions: Benefits of heavy-tailed mutations. CoRR, abs\/1805.10902, 2018."},{"key":"e_1_3_2_1_106_1","volume-title":"PPSN 2018","author":"Friedrich Tobias","year":"2018","unstructured":"[FGQW18b] Tobias Friedrich , Andreas G\u00f6bel , Francesco Quinzan , and Markus Wagner . Heavy-tailed mutation operators in single-objective combinatorial optimization. In Parallel Problem Solving from Nature , PPSN 2018 , Part I, pages 134--145. Springer , 2018 . [FGQW18b] Tobias Friedrich, Andreas G\u00f6bel, Francesco Quinzan, and Markus Wagner. Heavy-tailed mutation operators in single-objective combinatorial optimization. In Parallel Problem Solving from Nature, PPSN 2018, Part I, pages 134--145. Springer, 2018."},{"key":"e_1_3_2_1_107_1","doi-asserted-by":"publisher","DOI":"10.1162\/evco.2009.17.1.3"},{"key":"e_1_3_2_1_108_1","doi-asserted-by":"publisher","DOI":"10.1145\/1276958.1277194"},{"key":"e_1_3_2_1_109_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tcs.2008.08.021"},{"key":"e_1_3_2_1_110_1","first-page":"65","volume-title":"FOGA 2013","author":"Feldmann Matthias","year":"2013","unstructured":"[FK13] Matthias Feldmann and Timo K\u00f6tzing . Optimizing expected path lengths with ant colony optimization using fitness proportional update. In Foundations of Genetic Algorithms , FOGA 2013 , pages 65 -- 74 . ACM, 2013 . [FK13] Matthias Feldmann and Timo K\u00f6tzing. Optimizing expected path lengths with ant colony optimization using fitness proportional update. In Foundations of Genetic Algorithms, FOGA 2013, pages 65--74. ACM, 2013."},{"key":"e_1_3_2_1_111_1","doi-asserted-by":"publisher","DOI":"10.1145\/2908812.2908895"},{"key":"e_1_3_2_1_112_1","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2016.2613739"},{"key":"e_1_3_2_1_113_1","doi-asserted-by":"publisher","DOI":"10.1162\/EVCO_a_00159"},{"key":"e_1_3_2_1_114_1","doi-asserted-by":"publisher","DOI":"10.1145\/3205455.3205515"},{"key":"e_1_3_2_1_115_1","doi-asserted-by":"publisher","DOI":"10.1145\/3377930.3390200"},{"key":"e_1_3_2_1_116_1","first-page":"1113","volume-title":"GECCO 2004","author":"Fischer Simon","year":"2004","unstructured":"[FW04] Simon Fischer and Ingo Wegener . The Ising model on the ring: mutation versus recombination. In Genetic and Evolutionary Computation , GECCO 2004 , pages 1113 -- 1124 . Springer , 2004 . [FW04] Simon Fischer and Ingo Wegener. The Ising model on the ring: mutation versus recombination. In Genetic and Evolutionary Computation, GECCO 2004, pages 1113--1124. Springer, 2004."},{"key":"e_1_3_2_1_117_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tcs.2005.04.002"},{"key":"e_1_3_2_1_118_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00453-018-0429-2"},{"key":"e_1_3_2_1_119_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00453-015-0072-0"},{"key":"e_1_3_2_1_120_1","doi-asserted-by":"publisher","DOI":"10.1162\/evco.1999.7.2.173"},{"key":"e_1_3_2_1_121_1","doi-asserted-by":"publisher","DOI":"10.5555\/534133"},{"key":"e_1_3_2_1_122_1","first-page":"785","volume-title":"Genetic and Evolutionary Computation Conference, GECCO 2014","author":"Brian","year":"2014","unstructured":"[GP14] Brian W. Goldman and William F. Punch. Parameter-less population pyramid . In Genetic and Evolutionary Computation Conference, GECCO 2014 , pages 785 -- 792 . ACM, 2014 . [GP14] Brian W. Goldman and William F. Punch. Parameter-less population pyramid. In Genetic and Evolutionary Computation Conference, GECCO 2014, pages 785--792. ACM, 2014."},{"key":"e_1_3_2_1_123_1","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-36494-3_37"},{"key":"e_1_3_2_1_124_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00453-016-0214-z"},{"key":"e_1_3_2_1_125_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00453-017-0360-y"},{"key":"e_1_3_2_1_126_1","first-page":"62","volume-title":"PPSN 2006","author":"Hansen Nikolaus","year":"2006","unstructured":"[HGAK06] Nikolaus Hansen , Fabian Gemperle , Anne Auger , and Petros Koumoutsakos . When do heavy-tail distributions help? In Parallel Problem Solving from Nature , PPSN 2006 , pages 62 -- 71 . Springer , 2006 . [HGAK06] Nikolaus Hansen, Fabian Gemperle, Anne Auger, and Petros Koumoutsakos. When do heavy-tail distributions help? In Parallel Problem Solving from Nature, PPSN 2006, pages 62--71. Springer, 2006."},{"key":"e_1_3_2_1_127_1","first-page":"149","volume-title":"PPSN 1994","author":"Horn Jeffrey","year":"1994","unstructured":"[HGD94] Jeffrey Horn , David E. Goldberg , and Kalyanmoy Deb . Long path problems. In Parallel Problem Solving from Nature , PPSN 1994 , pages 149 -- 158 . Springer , 1994 . [HGD94] Jeffrey Horn, David E. Goldberg, and Kalyanmoy Deb. Long path problems. In Parallel Problem Solving from Nature, PPSN 1994, pages 149--158. Springer, 1994."},{"key":"e_1_3_2_1_128_1","doi-asserted-by":"publisher","DOI":"10.1145\/1389095.1389277"},{"key":"e_1_3_2_1_129_1","doi-asserted-by":"publisher","DOI":"10.1109\/4235.797971"},{"key":"e_1_3_2_1_130_1","doi-asserted-by":"publisher","DOI":"10.1145\/3205455.3205608"},{"key":"e_1_3_2_1_131_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0004-3702(01)00058-3"},{"key":"e_1_3_2_1_132_1","first-page":"41","volume-title":"PPSN 2008","author":"J\u00e4gersk\u00fcpper Jens","year":"2008","unstructured":"[J\u00e4g08] Jens J\u00e4gersk\u00fcpper . A blend of Markov-chain and drift analysis. In Parallel Problem Solving From Nature , PPSN 2008 , pages 41 -- 51 . Springer , 2008 . [J\u00e4g08] Jens J\u00e4gersk\u00fcpper. A blend of Markov-chain and drift analysis. In Parallel Problem Solving From Nature, PPSN 2008, pages 41--51. Springer, 2008."},{"key":"e_1_3_2_1_133_1","doi-asserted-by":"publisher","DOI":"10.5555\/1757524.1757528"},{"key":"e_1_3_2_1_134_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-17339-4"},{"key":"e_1_3_2_1_135_1","doi-asserted-by":"publisher","DOI":"10.1162\/106365605774666921"},{"key":"e_1_3_2_1_136_1","first-page":"87","volume-title":"FOGA 2013","author":"Jansen Thomas","year":"2013","unstructured":"[JOZ13] Thomas Jansen , Pietro S. Oliveto , and Christine Zarges . Approximating vertex cover using edge-based representations. In Foundations of Genetic Algorithms , FOGA 2013 , pages 87 -- 96 . ACM, 2013 . [JOZ13] Thomas Jansen, Pietro S. Oliveto, and Christine Zarges. Approximating vertex cover using edge-based representations. In Foundations of Genetic Algorithms, FOGA 2013, pages 87--96. ACM, 2013."},{"key":"e_1_3_2_1_137_1","doi-asserted-by":"publisher","DOI":"10.1145\/1068009.1068152"},{"key":"e_1_3_2_1_138_1","first-page":"25","volume-title":"FOCI 2007","author":"J\u00e4gersk\u00fcpper Jens","year":"2007","unstructured":"[JS07] Jens J\u00e4gersk\u00fcpper and Tobias Storch . When the plus strategy outperforms the comma strategy and when not. In Foundations of Computational Intelligence , FOCI 2007 , pages 25 -- 32 . IEEE, 2007 . [JS07] Jens J\u00e4gersk\u00fcpper and Tobias Storch. When the plus strategy outperforms the comma strategy and when not. In Foundations of Computational Intelligence, FOCI 2007, pages 25--32. IEEE, 2007."},{"key":"e_1_3_2_1_139_1","first-page":"89","volume-title":"PPSN 2000","author":"Jansen Thomas","year":"2000","unstructured":"[JW00] Thomas Jansen and Ingo Wegener . On the choice of the mutation probability for the (1+1) EA. In Parallel Problem Solving from Nature , PPSN 2000 , pages 89 -- 98 . Springer , 2000 . [JW00] Thomas Jansen and Ingo Wegener. On the choice of the mutation probability for the (1+1) EA. In Parallel Problem Solving from Nature, PPSN 2000, pages 89--98. Springer, 2000."},{"key":"e_1_3_2_1_140_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00453-002-0940-2"},{"key":"e_1_3_2_1_141_1","doi-asserted-by":"publisher","DOI":"10.5555\/1099040.1704883"},{"key":"e_1_3_2_1_142_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jda.2005.01.002"},{"key":"e_1_3_2_1_143_1","first-page":"1325","volume-title":"Genetic and Evolutionary Computation Conference, GECCO 2012","author":"Jansen Thomas","year":"2012","unstructured":"[JZ12] Thomas Jansen and Christine Zarges . Fixed budget computations: a different perspective on run time analysis. In Terence Soule and Jason H. Moore, editors , Genetic and Evolutionary Computation Conference, GECCO 2012 , pages 1325 -- 1332 . ACM, 2012 . [JZ12] Thomas Jansen and Christine Zarges. Fixed budget computations: a different perspective on run time analysis. In Terence Soule and Jason H. Moore, editors, Genetic and Evolutionary Computation Conference, GECCO 2012, pages 1325--1332. ACM, 2012."},{"key":"e_1_3_2_1_144_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tcs.2013.06.007"},{"key":"e_1_3_2_1_145_1","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2014.2349160"},{"key":"e_1_3_2_1_146_1","volume-title":"Genetic and Evolutionary Computation Conference, GECCO 2019","author":"Karavaev Vitalii","year":"2036","unstructured":"[KAD19] Vitalii Karavaev , Denis Antipov , and Benjamin Doerr . Theoretical and empirical study of the (1 + (\u03bb, \u03bb)) EA on the Leading-Ones problem . In Genetic and Evolutionary Computation Conference, GECCO 2019 , Companion Material, pages 2036 --2039. ACM, 2019. [KAD19] Vitalii Karavaev, Denis Antipov, and Benjamin Doerr. Theoretical and empirical study of the (1 + (\u03bb, \u03bb)) EA on the Leading-Ones problem. In Genetic and Evolutionary Computation Conference, GECCO 2019, Companion Material, pages 2036--2039. ACM, 2019."},{"key":"e_1_3_2_1_147_1","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2014.2308294"},{"key":"e_1_3_2_1_148_1","volume-title":"PPSN 2010","author":"Kratsch Stefan","year":"2010","unstructured":"[KLNO10] Stefan Kratsch , Per Kristian Lehre , Frank Neumann , and Pietro Simone Oliveto . Fixed parameter evolutionary algorithms and maximum leaf spanning trees: a matter of mutation. In Parallel Problem Solving from Nature , PPSN 2010 , Part I, pages 204--213. Springer , 2010 . [KLNO10] Stefan Kratsch, Per Kristian Lehre, Frank Neumann, and Pietro Simone Oliveto. Fixed parameter evolutionary algorithms and maximum leaf spanning trees: a matter of mutation. In Parallel Problem Solving from Nature, PPSN 2010, Part I, pages 204--213. Springer, 2010."},{"key":"e_1_3_2_1_149_1","first-page":"40","volume-title":"FOGA 2015","author":"K\u00f6tzing Timo","year":"2015","unstructured":"[KLW15] Timo K\u00f6tzing , Andrei Lissovoi , and Carsten Witt . (1+1) EA on generalized dynamic OneMax. In Foundations of Genetic Algorithms , FOGA 2015 , pages 40 -- 51 . ACM, 2015 . [KLW15] Timo K\u00f6tzing, Andrei Lissovoi, and Carsten Witt. (1+1) EA on generalized dynamic OneMax. In Foundations of Genetic Algorithms, FOGA 2015, pages 40--51. ACM, 2015."},{"key":"e_1_3_2_1_150_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00453-012-9660-4"},{"key":"e_1_3_2_1_151_1","doi-asserted-by":"publisher","DOI":"10.1145\/2001576.2001711"},{"key":"e_1_3_2_1_152_1","volume-title":"PPSN 2020","author":"K\u00f6tzing Timo","year":"2020","unstructured":"[KW20a] Timo K\u00f6tzing and Carsten Witt . Improved fixed-budget results via drift analysis. In Parallel Problem Solving from Nature , PPSN 2020 , Part II, pages 648--660. Springer , 2020 . [KW20a] Timo K\u00f6tzing and Carsten Witt. Improved fixed-budget results via drift analysis. In Parallel Problem Solving from Nature, PPSN 2020, Part II, pages 648--660. Springer, 2020."},{"key":"e_1_3_2_1_153_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tcs.2018.06.004"},{"key":"e_1_3_2_1_154_1","first-page":"244","volume-title":"PPSN 2010","author":"Lehre Per Kristian","year":"2010","unstructured":"[Leh10] Per Kristian Lehre . Negative drift in populations. In Parallel Problem Solving from Nature , PPSN 2010 , pages 244 -- 253 . Springer , 2010 . [Leh10] Per Kristian Lehre. Negative drift in populations. In Parallel Problem Solving from Nature, PPSN 2010, pages 244--253. Springer, 2010."},{"key":"e_1_3_2_1_155_1","doi-asserted-by":"publisher","DOI":"10.1145\/2001576.2001855"},{"key":"e_1_3_2_1_156_1","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2019.2917014"},{"key":"e_1_3_2_1_157_1","volume-title":"PPSN 2020","author":"Lengler Johannes","year":"2020","unstructured":"[LM20] Johannes Lengler and Jonas Meier . Large population sizes and crossover help in dynamic environments. In Parallel Problem Solving from Nature , PPSN 2020 , Part I, pages 610--622. Springer , 2020 . [LM20] Johannes Lengler and Jonas Meier. Large population sizes and crossover help in dynamic environments. In Parallel Problem Solving from Nature, PPSN 2020, Part I, pages 610--622. Springer, 2020."},{"key":"e_1_3_2_1_158_1","first-page":"94","volume-title":"ANALCO 2019","author":"Lengler Johannes","year":"2019","unstructured":"[LMS19] Johannes Lengler , Anders Martinsson , and Angelika Steger . When does hillclimbing fail on monotone functions: an entropy compression argument. In Analytic Algorithmics and Combinatorics , ANALCO 2019 , pages 94 -- 102 . SIAM, 2019 . [LMS19] Johannes Lengler, Anders Martinsson, and Angelika Steger. When does hillclimbing fail on monotone functions: an entropy compression argument. In Analytic Algorithmics and Combinatorics, ANALCO 2019, pages 94--102. SIAM, 2019."},{"key":"e_1_3_2_1_159_1","doi-asserted-by":"publisher","DOI":"10.1145\/3071178.3071317"},{"key":"e_1_3_2_1_160_1","first-page":"105","volume-title":"PPSN 2018","author":"Lehre Per Kristian","year":"2018","unstructured":"[LN18] Per Kristian Lehre and Phan Trung Hai Nguyen . Level-based analysis of the population-based incremental learning algorithm. In Parallel Problem Solving From Nature , PPSN 2018 , pages 105 -- 116 . Springer , 2018 . [LN18] Per Kristian Lehre and Phan Trung Hai Nguyen. Level-based analysis of the population-based incremental learning algorithm. In Parallel Problem Solving From Nature, PPSN 2018, pages 105--116. Springer, 2018."},{"key":"e_1_3_2_1_161_1","first-page":"154","volume-title":"FOGA 2019","author":"Lehre Per Kristian","year":"2019","unstructured":"[LN19a] Per Kristian Lehre and Phan Trung Hai Nguyen . On the limitations of the univariate marginal distribution algorithm to deception and where bivariate EDAs might help. In Foundations of Genetic Algorithms , FOGA 2019 , pages 154 -- 168 . ACM, 2019 . [LN19a] Per Kristian Lehre and Phan Trung Hai Nguyen. On the limitations of the univariate marginal distribution algorithm to deception and where bivariate EDAs might help. In Foundations of Genetic Algorithms, FOGA 2019, pages 154--168. ACM, 2019."},{"key":"e_1_3_2_1_162_1","doi-asserted-by":"publisher","DOI":"10.1145\/3321707.3321834"},{"key":"e_1_3_2_1_163_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33012322"},{"key":"e_1_3_2_1_164_1","doi-asserted-by":"publisher","DOI":"10.1162\/evco_a_00258"},{"key":"e_1_3_2_1_165_1","first-page":"181","volume-title":"FOGA 2011","author":"L\u00e4ssig J\u00f6rg","year":"2011","unstructured":"[LS11] J\u00f6rg L\u00e4ssig and Dirk Sudholt . Adaptive population models for offspring populations and parallel evolutionary algorithms. In Foundations of Genetic Algorithms , FOGA 2011 , pages 181 -- 192 . ACM, 2011 . [LS11] J\u00f6rg L\u00e4ssig and Dirk Sudholt. Adaptive population models for offspring populations and parallel evolutionary algorithms. In Foundations of Genetic Algorithms, FOGA 2011, pages 181--192. ACM, 2011."},{"key":"e_1_3_2_1_166_1","first-page":"52","volume-title":"FOGA 2015","author":"Lengler Johannes","year":"2015","unstructured":"[LS15] Johannes Lengler and Nicholas Spooner . Fixed budget performance of the (1+1) EA on linear functions. In Foundations of Genetic Algorithms , FOGA 2015 , pages 52 -- 61 . ACM, 2015 . [LS15] Johannes Lengler and Nicholas Spooner. Fixed budget performance of the (1+1) EA on linear functions. In Foundations of Genetic Algorithms, FOGA 2015, pages 52--61. ACM, 2015."},{"key":"e_1_3_2_1_167_1","doi-asserted-by":"publisher","DOI":"10.1017\/S0963548318000275"},{"key":"e_1_3_2_1_168_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00453-020-00778-4"},{"key":"e_1_3_2_1_169_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00453-012-9616-8"},{"key":"e_1_3_2_1_170_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00453-015-9975-z"},{"key":"e_1_3_2_1_171_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00500-010-0610-2"},{"key":"e_1_3_2_1_172_1","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2011.2112665"},{"key":"e_1_3_2_1_173_1","first-page":"87","volume-title":"Exponential slowdown for larger populations: the (&mu","author":"Lengler Johannes","year":"2019","unstructured":"[LZ19] Johannes Lengler and Xun Zou . Exponential slowdown for larger populations: the (&mu ; + 1)-EA on monotone functions. In Foundations of Genetic Algorithms, FOGA 2019 , pages 87 -- 101 . ACM , 2019. [LZ19] Johannes Lengler and Xun Zou. Exponential slowdown for larger populations: the (&mu; + 1)-EA on monotone functions. In Foundations of Genetic Algorithms, FOGA 2019, pages 87--101. ACM, 2019."},{"key":"e_1_3_2_1_174_1","first-page":"15","volume-title":"PPSN 1992","author":"M\u00fchlenbein Heinz","year":"1992","unstructured":"[M\u00fch92] Heinz M\u00fchlenbein . How genetic algorithms really work: mutation and hillclimbing. In Parallel Problem Solving from Nature , PPSN 1992 , pages 15 -- 26 . Elsevier , 1992 . [M\u00fch92] Heinz M\u00fchlenbein. How genetic algorithms really work: mutation and hillclimbing. In Parallel Problem Solving from Nature, PPSN 1992, pages 15--26. Elsevier, 1992."},{"key":"e_1_3_2_1_175_1","doi-asserted-by":"publisher","DOI":"10.1109\/CEC.2004.1330957"},{"key":"e_1_3_2_1_176_1","first-page":"25","article-title":"Expected fitness gains of randomized search heuristics for the traveling salesperson problem","author":"Nallaperuma Samadhi","year":"2017","unstructured":"[NNS17] Samadhi Nallaperuma , Frank Neumann , and Dirk Sudholt . Expected fitness gains of randomized search heuristics for the traveling salesperson problem . Evolutionary Computation , 25 , 2017 . [NNS17] Samadhi Nallaperuma, Frank Neumann, and Dirk Sudholt. Expected fitness gains of randomized search heuristics for the traveling salesperson problem. Evolutionary Computation, 25, 2017.","journal-title":"Evolutionary Computation"},{"key":"e_1_3_2_1_177_1","doi-asserted-by":"publisher","DOI":"10.1145\/1569901.1570016"},{"key":"e_1_3_2_1_178_1","volume-title":"PPSN 2010","author":"Neumann Frank","year":"2010","unstructured":"[NT10] Frank Neumann and Madeleine Theile . How crossover speeds up evolutionary algorithms for the multi-criteria all-pairs-shortest-path problem. In Parallel Problem Solving from Nature , PPSN 2010 , Part I, pages 667--676. Springer , 2010 . [NT10] Frank Neumann and Madeleine Theile. How crossover speeds up evolutionary algorithms for the multi-criteria all-pairs-shortest-path problem. In Parallel Problem Solving from Nature, PPSN 2010, Part I, pages 667--676. Springer, 2010."},{"key":"e_1_3_2_1_179_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tcs.2006.11.002"},{"key":"e_1_3_2_1_180_1","volume-title":"Bioinspired Computation in Combinatorial Optimization - Algorithms and Their Computational Complexity","author":"Neumann Frank","year":"2010","unstructured":"[NW10] Frank Neumann and Carsten Witt . Bioinspired Computation in Combinatorial Optimization - Algorithms and Their Computational Complexity . Springer , 2010 . [NW10] Frank Neumann and Carsten Witt. Bioinspired Computation in Combinatorial Optimization - Algorithms and Their Computational Complexity. Springer, 2010."},{"key":"e_1_3_2_1_181_1","first-page":"495","volume-title":"Genetic and Evolutionary Computation Conference, GECCO 2002","author":"Ochoa Gabriela","year":"2002","unstructured":"[Och02] Gabriela Ochoa . Setting the mutation rate: scope and limitations of the 1\/L heuristic . In Genetic and Evolutionary Computation Conference, GECCO 2002 , pages 495 -- 502 . Morgan Kaufmann , 2002 . [Och02] Gabriela Ochoa. Setting the mutation rate: scope and limitations of the 1\/L heuristic. In Genetic and Evolutionary Computation Conference, GECCO 2002, pages 495--502. Morgan Kaufmann, 2002."},{"key":"e_1_3_2_1_182_1","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2009.2014362"},{"key":"e_1_3_2_1_183_1","doi-asserted-by":"publisher","DOI":"10.1145\/3377930.3390212"},{"key":"e_1_3_2_1_184_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tcs.2018.07.007"},{"key":"e_1_3_2_1_185_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tcs.2015.01.002"},{"key":"e_1_3_2_1_186_1","volume-title":"Genetic and Evolutionary Computation Conference, GECCO 2009","author":"Posik Petr","year":"2009","unstructured":"[Pos09] Petr Posik . BBOB-benchmarking a simple estimation of distribution algorithm with Cauchy distribution . In Genetic and Evolutionary Computation Conference, GECCO 2009 , Companion Material, pages 2309--2314. ACM , 2009 . [Pos09] Petr Posik. BBOB-benchmarking a simple estimation of distribution algorithm with Cauchy distribution. In Genetic and Evolutionary Computation Conference, GECCO 2009, Companion Material, pages 2309--2314. ACM, 2009."},{"key":"e_1_3_2_1_187_1","volume-title":"Genetic and Evolutionary Computation Conference, GECCO 2010","author":"Pos\u00edk Petr","year":"2010","unstructured":"[Pos10] Petr Pos\u00edk . Comparison of Cauchy EDA and BIPOP-CMA-ES algorithms on the BBOB noiseless testbed . In Genetic and Evolutionary Computation Conference, GECCO 2010 , Companion Material, pages 1697--1702. ACM , 2010 . [Pos10] Petr Pos\u00edk. Comparison of Cauchy EDA and BIPOP-CMA-ES algorithms on the BBOB noiseless testbed. In Genetic and Evolutionary Computation Conference, GECCO 2010, Companion Material, pages 1697--1702. ACM, 2010."},{"key":"e_1_3_2_1_188_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tcs.2004.03.038"},{"key":"e_1_3_2_1_189_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00453-018-0488-4"},{"key":"e_1_3_2_1_190_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tcs.2013.09.036"},{"key":"e_1_3_2_1_191_1","doi-asserted-by":"publisher","DOI":"10.1162\/evco.1996.4.2.195"},{"key":"e_1_3_2_1_192_1","volume-title":"PPSN 2020","author":"Rajabi Amirhossein","year":"2020","unstructured":"[RW20a] Amirhossein Rajabi and Carsten Witt . Evolutionary algorithms with self-adjusting asymmetric mutation. In Parallel Problem Solving from Nature , PPSN 2020 , Part I, pages 664--677. Springer , 2020 . [RW20a] Amirhossein Rajabi and Carsten Witt. Evolutionary algorithms with self-adjusting asymmetric mutation. In Parallel Problem Solving from Nature, PPSN 2020, Part I, pages 664--677. Springer, 2020."},{"key":"e_1_3_2_1_193_1","doi-asserted-by":"publisher","DOI":"10.1145\/3377930.3389833"},{"key":"e_1_3_2_1_194_1","doi-asserted-by":"publisher","DOI":"10.1145\/3449639.3459336"},{"key":"e_1_3_2_1_195_1","first-page":"152","volume-title":"EvoCOP 2021","author":"Rajabi Amirhossein","year":"2021","unstructured":"[RW21b] Amirhossein Rajabi and Carsten Witt . Stagnation detection with randomized local search. In Evolutionary Computation in Combinatorial Optimization , EvoCOP 2021 , pages 152 -- 168 . Springer , 2021 . [RW21b] Amirhossein Rajabi and Carsten Witt. Stagnation detection with randomized local search. In Evolutionary Computation in Combinatorial Optimization, EvoCOP 2021, pages 152--168. Springer, 2021."},{"key":"e_1_3_2_1_196_1","first-page":"92","volume-title":"PPSN 2008","author":"Richter J. Neal","year":"2008","unstructured":"[RWP08] J. Neal Richter , Alden H. Wright , and John Paxton . Ignoble trails - where crossover is provably harmful. In Parallel Problem Solving from Nature , PPSN 2008 , pages 92 -- 101 . Springer , 2008 . [RWP08] J. Neal Richter, Alden H. Wright, and John Paxton. Ignoble trails - where crossover is provably harmful. In Parallel Problem Solving from Nature, PPSN 2008, pages 92--101. Springer, 2008."},{"key":"e_1_3_2_1_197_1","doi-asserted-by":"publisher","DOI":"10.1145\/2001576.2001692"},{"key":"e_1_3_2_1_198_1","doi-asserted-by":"publisher","DOI":"10.1016\/0375-9601(87)90796-1"},{"key":"e_1_3_2_1_199_1","first-page":"115","volume-title":"Foundations of Genetic Algorithms, FOGA","author":"Shapiro Jonathan L.","year":"2002","unstructured":"[Sha02] Jonathan L. Shapiro . The sensitivity of PBIL to its learning rate, and how detailed balance can remove it . In Foundations of Genetic Algorithms, FOGA 2002 , pages 115 -- 132 . Morgan Kaufmann , 2002. [Sha02] Jonathan L. Shapiro. The sensitivity of PBIL to its learning rate, and how detailed balance can remove it. In Foundations of Genetic Algorithms, FOGA 2002, pages 115--132. Morgan Kaufmann, 2002."},{"key":"e_1_3_2_1_200_1","doi-asserted-by":"publisher","DOI":"10.1162\/1063656053583414"},{"key":"e_1_3_2_1_201_1","first-page":"92","volume-title":"PPSN 2006","author":"Shapiro Jonathan L.","year":"2006","unstructured":"[Sha06] Jonathan L. Shapiro . Diversity loss in general estimation of distribution algorithms. In Parallel Problem Solving from Nature , PPSN 2006 , pages 92 -- 101 . Springer , 2006 . [Sha06] Jonathan L. Shapiro. Diversity loss in general estimation of distribution algorithms. In Parallel Problem Solving from Nature, PPSN 2006, pages 92--101. Springer, 2006."},{"key":"e_1_3_2_1_202_1","volume-title":"AAAI Conference on Artificial Intelligence, AAAI 2012","author":"Andrew","year":"2012","unstructured":"[SN12] Andrew M. Sutton and Frank Neumann. A parameterized runtime analysis of evolutionary algorithms for the Euclidean traveling salesperson problem . In AAAI Conference on Artificial Intelligence, AAAI 2012 . AAAI Press , 2012 . [SN12] Andrew M. Sutton and Frank Neumann. A parameterized runtime analysis of evolutionary algorithms for the Euclidean traveling salesperson problem. In AAAI Conference on Artificial Intelligence, AAAI 2012. AAAI Press, 2012."},{"key":"e_1_3_2_1_203_1","doi-asserted-by":"publisher","DOI":"10.1162\/EVCO_a_00119"},{"key":"e_1_3_2_1_204_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00453-011-9606-2"},{"key":"e_1_3_2_1_205_1","doi-asserted-by":"publisher","DOI":"10.1145\/1143997.1144099"},{"key":"e_1_3_2_1_206_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tcs.2007.06.008"},{"key":"e_1_3_2_1_207_1","doi-asserted-by":"publisher","DOI":"10.1162\/evco.2008.16.4.557"},{"key":"e_1_3_2_1_208_1","doi-asserted-by":"publisher","DOI":"10.1023\/B:JMMA.0000049379.14872.f5"},{"key":"e_1_3_2_1_209_1","doi-asserted-by":"publisher","DOI":"10.1145\/1068009.1068202"},{"key":"e_1_3_2_1_210_1","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2012.2202241"},{"key":"e_1_3_2_1_211_1","doi-asserted-by":"publisher","DOI":"10.1162\/EVCO_a_00171"},{"key":"e_1_3_2_1_212_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00453-020-00671-0"},{"key":"e_1_3_2_1_213_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00453-021-00809-8"},{"key":"e_1_3_2_1_214_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tcs.2004.03.047"},{"key":"e_1_3_2_1_215_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00453-018-0480-z"},{"key":"e_1_3_2_1_216_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-17517-6_31"},{"key":"e_1_3_2_1_217_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-31856-9_4"},{"key":"e_1_3_2_1_218_1","doi-asserted-by":"publisher","DOI":"10.1162\/106365606776022751"},{"key":"e_1_3_2_1_219_1","doi-asserted-by":"publisher","DOI":"10.1017\/S0963548312000600"},{"key":"e_1_3_2_1_220_1","doi-asserted-by":"publisher","DOI":"10.1145\/2576768.2598237"},{"key":"e_1_3_2_1_221_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00453-018-0463-0"},{"key":"e_1_3_2_1_222_1","first-page":"1452","volume-title":"Genetic and Evolutionary Computation Conference, GECCO 2007","author":"Richard","year":"2007","unstructured":"[WJ07] Richard A. Watson and Thomas Jansen. A building-block royal road where crossover is provably essential . In Genetic and Evolutionary Computation Conference, GECCO 2007 , pages 1452 -- 1459 . ACM, 2007 . [WJ07] Richard A. Watson and Thomas Jansen. A building-block royal road where crossover is provably essential. In Genetic and Evolutionary Computation Conference, GECCO 2007, pages 1452--1459. ACM, 2007."},{"key":"e_1_3_2_1_223_1","volume-title":"ICIC 2018","author":"Wu Mengxi","year":"2018","unstructured":"[WQT18] Mengxi Wu , Chao Qian , and Ke Tang . Dynamic mutation based Pareto optimization for subset selection. In Intelligent Computing Methodologies , ICIC 2018 , Part III, pages 25--35. Springer , 2018 . [WQT18] Mengxi Wu, Chao Qian, and Ke Tang. Dynamic mutation based Pareto optimization for subset selection. In Intelligent Computing Methodologies, ICIC 2018, Part III, pages 25--35. Springer, 2018."},{"key":"e_1_3_2_1_224_1","doi-asserted-by":"publisher","DOI":"10.5555\/647901.738817"},{"key":"e_1_3_2_1_225_1","doi-asserted-by":"publisher","DOI":"10.1109\/4235.771163"}],"event":{"name":"GECCO '21: Genetic and Evolutionary Computation Conference","sponsor":["SIGEVO ACM Special Interest Group on Genetic and Evolutionary Computation"],"location":"Lille France","acronym":"GECCO '21"},"container-title":["Proceedings of the Genetic and Evolutionary Computation Conference Companion"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3449726.3461406","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3449726.3461406","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:18:34Z","timestamp":1750191514000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3449726.3461406"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,7]]},"references-count":225,"alternative-id":["10.1145\/3449726.3461406","10.1145\/3449726"],"URL":"https:\/\/doi.org\/10.1145\/3449726.3461406","relation":{},"subject":[],"published":{"date-parts":[[2021,7,7]]},"assertion":[{"value":"2021-07-08","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}