IJPAM: Volume 91, No. 3 (2014)

SOLVING A MINIMIZATION PROBLEM FOR A CLASS OF
CONSTRAINED MAXIMUM EIGENVALUE FUNCTION

Wei Wang$^1$, Miao Chen$^2$, Lingling Zhang$^3$
$^1$School of Mathematics Liaoning Normal University
Liaoning, Dalian, 116029, P.R. CHINA
$^2$School of Mathematics Liaoning Normal University
Liaoning, Dalian, 116029, P.R. CHINA


Abstract. Nonsmooth convex optimization problem is a class of important problems in operational research. Bundle methods are considered as one of the most efficient methods for solving nonsmooth optimization problems. The methods have already been applied to many practical problems. In this paper, using bundle method, the optimization problem that the sum of maximum eigenvalue function and general non-smooth convex function can be solved. Through approximation to the objective function, the proximal bundle method based on approximate model is given. We prove that the sequences generated by the algorithm converge to the optimal solution of the original problem. Finally, the algorithm is used to solve a class of constrained maximum eigenvalue function.

Received: August 28, 2013

AMS Subject Classification: 15A18, 49J52, 52A41

Key Words and Phrases: nonsmooth optimization, bundle method, maximum eigenvalue function

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DOI: 10.12732/ijpam.v91i3.2 How to cite this paper?
Source:
International Journal of Pure and Applied Mathematics
ISSN printed version: 1311-8080
ISSN on-line version: 1314-3395
Year: 2014
Volume: 91
Issue: 3