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Titlebook: Artificial Evolution; 13th International C Evelyne Lutton,Pierrick Legrand,Marc Schoenauer Conference proceedings 2018 Springer Internation

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發(fā)表于 2025-3-21 16:45:12 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱(chēng)Artificial Evolution
期刊簡(jiǎn)稱(chēng)13th International C
影響因子2023Evelyne Lutton,Pierrick Legrand,Marc Schoenauer
視頻videohttp://file.papertrans.cn/163/162018/162018.mp4
學(xué)科分類(lèi)Lecture Notes in Computer Science
圖書(shū)封面Titlebook: Artificial Evolution; 13th International C Evelyne Lutton,Pierrick Legrand,Marc Schoenauer Conference proceedings 2018 Springer Internation
影響因子.This book constitutes the thoroughly refereed post-conference?proceedings of the 13th International Conference on Artificial Evolution, EA 2017, held in Paris, France, in October 2017...?The 16 revised papers were carefully reviewed and selected from 33?submissions. The papers cover a wide range of topics in the field of artificial evolution, such as evolutionary computation, evolutionary optimization, co-evolution, artificial life, population dynamics, theory, algorithmics and modeling, implementations, application of evolutionary paradigms to the real world?(industry, biosciences, ...), other biologically-inspired paradigms (swarm, artificial ants, artificial immune systems, cultural algorithms...), memetic algorithms, multi-objective optimisation, constraint handling, parallel algorithms,, dynamic optimization, machine learning and hybridization with?other soft computing techniques..
Pindex Conference proceedings 2018
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https://doi.org/10.1007/978-3-319-78133-4artificial intelligence; assignment problems; combinatorial mathematics; combinatorial optimization; evo
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S. Ruhl,G. C. Begley,M. Bickel,H. Pluzniksolution or it is discarded. One of the most studied local search algorithms is simulated annealing. It often uses the Metropolis condition as acceptance criterion, which always accepts equal or better quality solutions and worse ones with a probability that depends on the amount of worsening and a
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S. Ruhl,G. C. Begley,M. Bickel,H. Pluznikch. We particularly focus on establishing links between the structure of optimization problems and the efficiency of such local search algorithms. In our experiments we compare partial neighborhood local searches to state-of-the-art tabu search and iterated local search and perform a parameter sensi
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S. Ruhl,G. C. Begley,M. Bickel,H. PluznikMSA, for ., coded using the EASEA platform. This approach evolves individual sub-alignments called “patches” that are used to create a new kind of Multiple Sequence Alignment where alternative solutions are computed simultaneously using different fitness functions. Solutions are generated by combini
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