Handbook on Semidefinite, Conic and Polynomial Optimization

ISBN: 9781489978035

$279.00 $237.15

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 doctoralstudents, 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.
Title:
Handbook on Semidefinite, Conic and Polynomial Optimization
ISBN-13:
9781489978035
Author:
Publisher:
Springer US
Published Date:
20160823
Edition:
1
Binding
Paperback / softback
Pages:
960
Language:
English
Product Dim.:
9.25 H x 6.10 W (inches)

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