Improved DC Programming
Approaches for Solving the Quadratic Eigenvalue Complementarity
Problem
Yi-Shuai Niu, J.
Judice, Hoai An Le Thi and Dinh Tao Pham
Abstract
In
this paper, we discuss the solution of a Quadratic Eigenvalue
Complementarity Problem (QEiCP) by using Difference of Convex (DC)
programming approaches. We first show that QEiCP can be represented as
DC programming problem. Then we investigate different DC programming
formulations of QEiCP and discuss their DC algorithms based on a
well-known method - DCA. A new local dc decomposition is proposed which
aims at constructing a better DC decomposition regarding to the
specific feature of the target problem in some neighborhoods of the
iterates. This new procedure yields faster convergence and better
precision of the computed solution. Numerical results illustrate the
efficiency of the new DC algorithms in practice.