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Titlebook: Optimization in Artificial Intelligence and Data Sciences; ODS, First Hybrid Co Lavinia Amorosi,Paolo Dell’Olmo,Isabella Lari Conference pr

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書目名稱Optimization in Artificial Intelligence and Data Sciences
副標(biāo)題ODS, First Hybrid Co
編輯Lavinia Amorosi,Paolo Dell’Olmo,Isabella Lari
視頻videohttp://file.papertrans.cn/704/703243/703243.mp4
概述Contributes to ameliorating methodological methods for both linear, combinatorial and nonlinear optimization problems.Provides new optimization solutions on a number of healthcare problems related to
叢書名稱AIRO Springer Series
圖書封面Titlebook: Optimization in Artificial Intelligence and Data Sciences; ODS, First Hybrid Co Lavinia Amorosi,Paolo Dell’Olmo,Isabella Lari Conference pr
描述.This book is addressed to researchers in operations research, data science and artificial intelligence. It collects selected contributions from the first hybrid “Optimization and Decision Science - ODS2021” international conference on the theme Optimization and Artificial Intelligence and Data Sciences, which was held in Rome 14-17 September 2021 and organized by AIRO, the Italian Operations Research Society and the Department of Statistical Sciences of Sapienza University of Rome. ..The book offers new and original contributions on different methodological optimization topics, from Support Vector Machines to Game Theory Network Models, from Mathematical Programming to Heuristic Algorithms, and Optimization Methods for a number of emerging problems from Truck and Drone delivery to Risk Assessment, from Power Networks Design to Portfolio Optimization. The articles in the book can give a significant edge to the general themes of sustainability and pollution reduction, distributive logistics, healthcare management in pandemic scenarios and clinical trials, distributed computing, scheduling, and many others. .For these reasons, the book is aimed not only at researchers in the Operatio
出版日期Conference proceedings 2022
關(guān)鍵詞Operation Research; Discrete optimization; Multiple criteria decision making; Heuristics; Decision makin
版次1
doihttps://doi.org/10.1007/978-3-030-95380-5
isbn_softcover978-3-030-95382-9
isbn_ebook978-3-030-95380-5Series ISSN 2523-7047 Series E-ISSN 2523-7055
issn_series 2523-7047
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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