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Titlebook: Metaheuristics; 14th International C Luca Di Gaspero,Paola Festa,Mario Pavone Conference proceedings 2023 The Editor(s) (if applicable) and

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發(fā)表于 2025-3-21 16:49:46 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Metaheuristics
副標(biāo)題14th International C
編輯Luca Di Gaspero,Paola Festa,Mario Pavone
視頻videohttp://file.papertrans.cn/632/631359/631359.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Metaheuristics; 14th International C Luca Di Gaspero,Paola Festa,Mario Pavone Conference proceedings 2023 The Editor(s) (if applicable) and
描述This book constitutes the refereed proceedings of the 14th International Conference on Metaheuristics, MIC 2022, held in Syracuse, Italy, in July 2022..The 48 full papers together with 17 short papers presented were carefully reviewed and selected from 72 submissions. The papers detail metaheuristic techniques..Chapter “Evaluating the Effects of Chaos in Variable Neighbourhood Search” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com..
出版日期Conference proceedings 2023
關(guān)鍵詞artificial intelligense; combinatorial optimization; computer networks; computer science; computer syste
版次1
doihttps://doi.org/10.1007/978-3-031-26504-4
isbn_softcover978-3-031-26503-7
isbn_ebook978-3-031-26504-4Series 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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Conference proceedings 2023..The 48 full papers together with 17 short papers presented were carefully reviewed and selected from 72 submissions. The papers detail metaheuristic techniques..Chapter “Evaluating the Effects of Chaos in Variable Neighbourhood Search” is available open access under a Creative Commons Attribution
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Optimizing Multi-variable Time Series Forecasting Using Metaheuristics,t to improve the overall performance. The resulting environment is compared with other solutions that use only the same type of predictor for each variable. Finally, we can assert that using a multi-agent environment can improve the performance, accuracy, and generalization of our model.
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0302-9743 July 2022..The 48 full papers together with 17 short papers presented were carefully reviewed and selected from 72 submissions. The papers detail metaheuristic techniques..Chapter “Evaluating the Effects of Chaos in Variable Neighbourhood Search” is available open access under a Creative Commons At
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發(fā)表于 2025-3-23 07:21:32 | 只看該作者
,Unsupervised Machine Learning for?the?Quadratic Assignment Problem,roblem instances. Negative results of the proposed learning mechanism are reported for other instances. This result contrasts with other hard optimization problems for which efficient learning processes are known in the context of local search.
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