Published in

Elsevier, Linear Algebra and its Applications, 1(433), p. 41-51, 2010

DOI: 10.1016/j.laa.2010.02.008

Links

Tools

Export citation

Search in Google Scholar

How to project onto an isotone projection cone

Journal article published in 2010 by A. B. Németh, S. Z. Nemeth, S. Z. Németh
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

Full text: Download

Green circle
Preprint: archiving allowed
Orange circle
Postprint: archiving restricted
Red circle
Published version: archiving forbidden
Data provided by SHERPA/RoMEO

Abstract

The solution of the complementarity problem defined by a mapping f:Rn→Rn and a cone K⊂Rn consists of finding the fixed points of the operator PK∘(I-f), where PK is the projection onto the cone K and I stands for the identity mapping. For the class of isotone projection cones (cones admitting projections isotone with respect to the order relation they generate) and f satisfying certain monotonicity properties, the solution can be obtained by iterative processes (see G. Isac, A.B. Németh, Projection methods, isotone projection cones, and the complementarity problem, J. Math. Anal. Appl. 153(1) (1990) 258–275 and S.Z. Németh, Iterative methods for nonlinear complementarity problems on isotone projection cones, J. Math. Anal. Appl. 350(1) (2009) 340–347). These algorithms require computing at each step the projection onto the cone K. In general, computing the projection mapping onto a cone K is a difficult and computationally expensive problem. In this note it is shown that the projection of an arbitrary point onto an isotone projection cone in Rn can be obtained by projecting recursively at most n-1 times into subspaces of decreasing dimension. This emphasizes the efficiency of the algorithms mentioned above and furnishes a handy tool for some problems involving special isotone projection cones, as for example the non-negative monotone cones occurring in reconstruction problems (see e.g. Section 5.13 in J. Dattorro, Convex Optimization and Euclidean Distance Geometry, Meboo, 2005, v2009.04.11).