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Titlebook: Discrete Diversity and Dispersion Maximization; A Tutorial on Metahe Rafael Martí,Anna Martínez-Gavara Book 2023 The Editor(s) (if applicab

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書目名稱Discrete Diversity and Dispersion Maximization
副標(biāo)題A Tutorial on Metahe
編輯Rafael Martí,Anna Martínez-Gavara
視頻videohttp://file.papertrans.cn/282/281089/281089.mp4
概述Basic principles and fundamental ideas of successful methodologies for discrete optimization.Allows the readers to create their own applications to other discrete optimization problems through tutoria
叢書名稱Springer Optimization and Its Applications
圖書封面Titlebook: Discrete Diversity and Dispersion Maximization; A Tutorial on Metahe Rafael Martí,Anna Martínez-Gavara Book 2023 The Editor(s) (if applicab
描述.This book demonstrates the metaheuristic methodologies that apply to maximum diversity problems to solve them. Maximum diversity problems arise in many practical settings from facility location to social network analysis and constitute an important class of NP-hard problems in combinatorial optimization. In fact, this volume presents a “missing link” in the combinatorial optimization-related literature. In providing the basic principles and fundamental ideas of the most successful methodologies for discrete optimization, this book allows readers to create their own applications for other discrete optimization problems. Additionally, the book is designed to be useful and accessible to researchers and practitioners in management science, industrial engineering, economics, and computer science, while also extending value to non-experts in combinatorial optimization. Owed to the tutorials presented in each chapter, this book may be used in a master course, a doctoral seminar, or as supplementary to a primary text in upper undergraduate courses..The chapters are divided into three main sections. The first section describes a metaheuristic methodology in a tutorial style, offering gener
出版日期Book 2023
關(guān)鍵詞Metaheuristics; discrete diversity; math programming models; branch and bound; integer programming; Greed
版次1
doihttps://doi.org/10.1007/978-3-031-38310-6
isbn_softcover978-3-031-38312-0
isbn_ebook978-3-031-38310-6Series ISSN 1931-6828 Series E-ISSN 1931-6836
issn_series 1931-6828
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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Book 2023ny practical settings from facility location to social network analysis and constitute an important class of NP-hard problems in combinatorial optimization. In fact, this volume presents a “missing link” in the combinatorial optimization-related literature. In providing the basic principles and fund
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Variable Neighborhood Searchy be exploited and show how they can be organized within variable neighborhood descent and variable neighborhood search heuristics. Finally, we provide insights on the performance of different VNS methodologies applied to two diversity problems: the maximum diversity problem and the capacitated dispersion problem.
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Less Is More Approachst introduced to solve two diversity problems. In this chapter we present its general principles, and describe how it was used to solve the Max-Mean diversity problem in 2017 and minimum-differential dispersion problem in 2016.
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