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Titlebook: Evolutionary Computation in Combinatorial Optimization; 24th European Confer Thomas Stützle,Markus Wagner Conference proceedings 2024 The E

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發(fā)表于 2025-3-21 18:58:26 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Evolutionary Computation in Combinatorial Optimization
副標(biāo)題24th European Confer
編輯Thomas Stützle,Markus Wagner
視頻videohttp://file.papertrans.cn/318/317877/317877.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Evolutionary Computation in Combinatorial Optimization; 24th European Confer Thomas Stützle,Markus Wagner Conference proceedings 2024 The E
描述.This book constitutes the referred proceedings of the 24th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2024, held as part of EvoStar 2024, in Aberystwyth, UK, during April 3–5, 2024...The 12 full papers presented in this book were carefully reviewed and selected from 28 submissions. They cover a variety?of topics, ranging from constructive algorithms, machine learning techniques?ranging from neural network based guidance to sparse surrogate models for optimization?problems, the foundation of evolutionary computation algorithms and?other search heuristics, to multi-objective optimization problems.?.
出版日期Conference proceedings 2024
關(guān)鍵詞Metaheuristics; Combinatorial optimization problems; Evolutionary Algorithms ; Swarm Intelligence ; Loca
版次1
doihttps://doi.org/10.1007/978-3-031-57712-3
isbn_softcover978-3-031-57711-6
isbn_ebook978-3-031-57712-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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Diego de Matos Gondim,Roger Miarka MAX-SAT problems compared to results on random NK landscapes. We show that Partition Crossover induces hypercube lattices over subsets of local optima; all of the local optima which appear in a lattice can be evaluated with a single linear equation.
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Vincenzo Matera,Angela Biscaldiproach by comparing the enhanced . with the original ., using two benchmark sets from the literature. We show that the results of the enhanced . significantly improve over the original results, especially when tackling instances with non-uniformly generated input strings.
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