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Projection Methods in Conic Optimization

  • Didier Henrion
  • Jérôme Malick
Chapter
Part of the International Series in Operations Research & Management Science book series (ISOR, volume 166)

Abstract

There exist efficient algorithms to project a point onto the intersection of a convex conic and an affine subspace. Those conic projections are in turn the work-horse of a range of algorithms in conic optimization, having a variety of applications in science, finance and engineering. This chapter reviews some of these algorithms, emphasizing the so-called regularization algorithms for linear conic optimization, and applications in polynomial optimization. This is a presentation of the material of several recent research articles; we aim here at clarifying the ideas, presenting them in a general framework, and pointing out important techniques.

Keywords

Regularization Method Alternate Direction Method Polynomial Optimization Conic Projection Regularization Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgement

The work of the first author was partly supported by research project 103/10/0628 of the Grant Agency of the Czech Republic and research programme MSM6840770038 of the Ministry of Education of the Czech Republic.

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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  1. 1.CNRS, LAAS, ToulouseToulouseFrance
  2. 2.Faculty of Electrical EngineeringCzech Technical University in PraguePragueCzech Republic
  3. 3.CNRS, LJK, Grenoble, INRIASaint IsmierFrance

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