  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.
