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Titlebook: Evolutionary Computation in Combinatorial Optimization; 20th European Confer Luís Paquete,Christine Zarges Conference proceedings 2020 Spri

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書目名稱Evolutionary Computation in Combinatorial Optimization
副標(biāo)題20th European Confer
編輯Luís Paquete,Christine Zarges
視頻videohttp://file.papertrans.cn/318/317874/317874.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Evolutionary Computation in Combinatorial Optimization; 20th European Confer Luís Paquete,Christine Zarges Conference proceedings 2020 Spri
描述.This book constitutes the refereed proceedings of the 20th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2020, held as part of Evo*2020, in Seville, Spain, in April 2020, co-located with the Evo*2020 events EuroGP, EvoMUSART and EvoApplications..The 14 full papers presented in this book were carefully reviewed and selected from 37 submissions. The papers cover a wide spectrum of topics, ranging from the foundations of evolutionary computation algorithms and other search heuristics, to their accurate design and application to combinatorial optimization problems..
出版日期Conference proceedings 2020
關(guān)鍵詞combinatorial optimization; computer networks; computer science; computer systems; correlation analysis;
版次1
doihttps://doi.org/10.1007/978-3-030-43680-3
isbn_softcover978-3-030-43679-7
isbn_ebook978-3-030-43680-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2020
The information of publication is updating

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Bildungstransmission in Migrantenfamilienevolutionary algorithms no better run time guarantee than . is known, so our result rather suggests that the UMDA can cope well with deception and epistatis..Together with the result of Lehre and Nguyen, our result for the first time rigorously proves that running EDAs in the regime with genetic drift can lead to drastic performance losses.
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,Die Reform des Staatsbürgerschaftsrechts, non-dominated solutions in the population. The new features are tested by studying the population changes on the Adaptive .-Sampling .-Hood while solving 30 instances of a 3 objective, 100 variables MNK-landscape problem. We also discuss the behavior of the auxiliary model and the quality of its hypervolume estimations.
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J?rg Hagedorn,Verena Schurt,Wiebke Waburgthors. In a benchmark study, it can be shown that the way in which population management is performed is important to enhance the solution quality of the GGA. On average, the best GGA variant is 2.43% worse than the best known solution.
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