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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:
Inhaltsverzeichnis
From the reviews:
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. This is an advanced book and particularly in the theory section . The papers in this volume will be of interest to advanced graduate students and researchers working in conic optimization, SDP, and polynomial optimization. (Brian Borchers, The Mathematical Association of America, June, 2012)
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