Authors:
- Discuss some important subclasses of polynomial optimization models arising from various applications
- Focuses on approximations algorithms with guaranteed worst case performance analysis
- Presents a clear view of the basic ideas underlying the design of algorithms and the benefits are highlighted by illustrative examples showing the possible applications
- Includes supplementary material: sn.pub/extras
Part of the book series: SpringerBriefs in Optimization (BRIEFSOPTI)
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Table of contents (5 chapters)
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Front Matter
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Back Matter
About this book
Polynomial optimization have been a hot research topic for the past few years and its applications range from Operations Research, biomedical engineering, investment science, to quantum mechanics, linear algebra, and signal processing, among many others. In this brief the authors discuss some important subclasses of polynomial optimization models arising from various applications, with a focus on approximations algorithms with guaranteed worst case performance analysis. The brief presents a clear view of the basic ideas underlying the design of such algorithms and the benefits are highlighted by illustrative examples showing the possible applications.
This timely treatise will appeal to researchers and graduate students in the fields of optimization, computational mathematics, Operations Research, industrial engineering, and computer science.
Reviews
From the reviews:
“The book is an outgrowth of the first author’s Ph.D. thesis, defended in 2011 … . It is a well-written timely collection of state-of-the-art approximation algorithms for polynomial optimization problems … . All of the approximation results of the book are conveniently summarized and listed in table 5.1 for quick reference, with a unified nomenclature introduced in sections 1.3.1 and 1.3.2.” (Didier Henrion, Mathematical Reviews, March, 2013)Authors and Affiliations
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, Mathematics, Shanghai University, Shanghai, China, People's Republic
Zhening Li
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, Management Sciences, City University of Hong Kong, Kowloon Tong, Hong Kong SAR
Simai He
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, Industrial & Systems Engineering, University of Minnesota, Minneapolis, USA
Shuzhong Zhang
Bibliographic Information
Book Title: Approximation Methods for Polynomial Optimization
Book Subtitle: Models, Algorithms, and Applications
Authors: Zhening Li, Simai He, Shuzhong Zhang
Series Title: SpringerBriefs in Optimization
DOI: https://doi.org/10.1007/978-1-4614-3984-4
Publisher: Springer New York, NY
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Zhening Li, Simai He,Shuzhong Zhang 2012
Softcover ISBN: 978-1-4614-3983-7Published: 24 July 2012
eBook ISBN: 978-1-4614-3984-4Published: 25 July 2012
Series ISSN: 2190-8354
Series E-ISSN: 2191-575X
Edition Number: 1
Number of Pages: VIII, 124
Topics: Optimization, Mathematical Modeling and Industrial Mathematics, Algorithms, Applications of Mathematics