Projection Methods in Conic Optimization

Didier Henrion () and Jérôme Malick ()
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Didier Henrion: CNRS, LAAS, Toulouse
Jérôme Malick: CNRS, LJK, Grenoble, INRIA

Chapter Chapter 20 in Handbook on Semidefinite, Conic and Polynomial Optimization, 2012, pp 565-600 from Springer

Abstract: 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 (search for similar items in EconPapers)
Date: 2012
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DOI: 10.1007/978-1-4614-0769-0_20

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