Overview
- Broadens understanding of nonlinear combinatorial optimization applications to machine learning, social computing, cloud computing, wireless communication, and data science
- Features articles by leading experts in nonlinear combinatorial optimization
- Outlines theoretical developments which utilize Newton methods submodular optimization, and non-submodular maximization
Part of the book series: Springer Optimization and Its Applications (SOIA, volume 147)
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Table of contents (16 chapters)
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Front Matter
Keywords
- discrete convex analysis
- discrete Newton methods
- primal-dual methods with convex relaxation
- submodular optimization
- optimization in data network designs
- spanning tree in wireless networks
- scheduling with energy allocation
- convex relaxation
- combinatorial optimization
- homogeneous sensor systems
- nonlinear function
- heterogeneous sensor systems
- nonlinear assignment problems
- Fractional Integer Progmanmming
- optimization in machine learning
- combinatorics
About this book
Graduate students and researchers in applied mathematics, optimization, engineering, computer science, and management science will find this book a useful reference which provides an introduction to applications and fundamental theories in nonlinear combinatorial optimization. Nonlinear combinatorial optimization is a new research area within combinatorial optimization and includes numerous applications to technological developments, such as wireless communication, cloud computing, data science, and social networks. Theoretical developments including discrete Newton methods, primal-dual methods with convex relaxation, submodular optimization, discrete DC program, along with several applications are discussed and explored in this book through articles by leading experts.
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Editors and Affiliations
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Bibliographic Information
Book Title: Nonlinear Combinatorial Optimization
Editors: Ding-Zhu Du, Panos M. Pardalos, Zhao Zhang
Series Title: Springer Optimization and Its Applications
DOI: https://doi.org/10.1007/978-3-030-16194-1
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Nature Switzerland AG 2019
Hardcover ISBN: 978-3-030-16193-4Published: 14 June 2019
Softcover ISBN: 978-3-030-16196-5Published: 14 August 2020
eBook ISBN: 978-3-030-16194-1Published: 31 May 2019
Series ISSN: 1931-6828
Series E-ISSN: 1931-6836
Edition Number: 1
Number of Pages: VIII, 315
Number of Illustrations: 20 b/w illustrations, 9 illustrations in colour
Topics: Calculus of Variations and Optimal Control; Optimization, Data Structures and Information Theory, Combinatorics, Convex and Discrete Geometry, Algorithms, Topology