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Download Handbook on Semidefinite, Conic and Polynomial Optimization (International Series in Operations Research Management Science) fb2, epub

by Miguel F. Anjos,Jean B. Lasserre

Download Handbook on Semidefinite, Conic and Polynomial Optimization (International Series in Operations Research  Management Science) fb2, epub

ISBN: 1461407680
Author: Miguel F. Anjos,Jean B. Lasserre
Language: English
Publisher: Springer; 2012 edition (November 18, 2011)
Pages: 960
Category: Processes & Infrastructure
Subcategory: Money
Rating: 4.8
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Size Fb2: 1679 kb
Size ePub: 1548 kb
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Although semidefinite optimization has been studied (under different names) since at least the 1940s, its importance grew immensely during the 1990s after polynomial-time interior-point. Handbook on Semidefinite, Conic and Polynomial Optimization. Individual sections covering theory, algorithms, software and applications.

Conic optimization refers to the problem of optimizing a linear function over the intersection of an affine space and a closed convex cone

Conic optimization refers to the problem of optimizing a linear function over the intersection of an affine space and a closed convex cone. We focus particularly on the special case where the cone is chosen as the cone of positive semidefinite matrices for which the resulting optimization problem is called a semidefinite optimization problem.

Although semidefinite optimization has been studied (under different names) since at least.

Miguel F. Anjos, Jean B. Lasserre. Springer Science & Business Media, 1. 1. Anjos & Jean B. Lasserre (e., 2012. Handle: RePEc:spr:isorms:978-1-4614-0769-0 DOI: 1. 0.

Positivity and optimization: beyond polynomials, Jean B. Lasserre and Mihai Putinar - Self-regular interior-point methods for semidefinite . File: PDF, . 7 MB. Читать онлайн. Lasserre and Mihai Putinar - Self-regular interior-point methods for semidefinite optimization, Maziar Salahi and Tamás Terlaky - Elementary optimality conditions for nonlinear SDPs, Florian Jarre - Recent progress in interior-point methods: cutting-plane algorithms and warm starts, Alexander Engau - Exploiting sparsity in SDP relaxation of polynomial optimization problems .

Автор: Anjos Название: Handbook on Semidefinite, Conic and Polynomial Optimization ISBN: 1461407680 .

from book Handbook of Semidefinite, Conic and Polynomial Optimization. trix completion problem and the related semidefinite completion problem, see. the classic paper on semidefinite completion, and follow-up papers. Article · August 2010 with 216 Reads. How we measure 'reads'. and ; also see on the topic of the complexity of these completion.

Meeting Name: Congrès Belge de la Route gnd. Personal Name: Anjos, Miguel F. Sonstige (DE-588)1019223219. Rubrics: Semidefinite Optimierung.

This volume is a collection of self contained survey papers on various aspects of semidefinite programming and polynomial optimization. The volume is divided into four sections, covering the theory of conic and polynomial optimization, algorithms, software implementations, and applications of semidefinite and polynomial optimization. The theory section contains several interesting papers on aspects of the semidefinite programming approach to polynomial optimization. The section on algorithms includes a survey on self regular interior point methods for SDP.

Semidefinite and conic optimization is a major and thriving research area within the optimization community. Although semidefinite optimization has been studied (under different names) since at least the 1940s, its importance grew immensely during the 1990s after polynomial-time interior-point methods for linear optimization were extended to solve semidefinite optimization problems.

Since the beginning of the 21st century, not only has research into semidefinite and conic optimization continued unabated, but also a fruitful interaction has developed with algebraic geometry through the close connections between semidefinite matrices and polynomial optimization. This has brought about important new results and led to an even higher level of research activity.

This Handbook on Semidefinite, Conic and Polynomial Optimization provides the reader with a snapshot of the state-of-the-art in the growing and mutually enriching areas of semidefinite optimization, conic optimization, and polynomial optimization. It contains a compendium of the recent research activity that has taken place in these thrilling areas, and will appeal to doctoral students, young graduates, and experienced researchers alike.

The Handbook’s thirty-one chapters are organized into four parts:

Theory, covering significant theoretical developments as well as the interactions between conic optimization and polynomial optimization;Algorithms, documenting the directions of current algorithmic development;Software, providing an overview of the state-of-the-art;Applications, dealing with the application areas where semidefinite and conic optimization has made a significant impact in recent years.

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