Efficient DC programming approaches for the asymmetric eigenvalue complementarity problem

Y. S. Niu, T. Pham Dinh, H. A. Le Thi and J. J. Júdice

Abstract

In this paper, we propose nonlinear programming formulations (NLP) and DC (Difference of Convex functions) programming approaches for the asymmetric eigenvalue complementarity problem (EiCP). The EiCP has a solution if and only if these NLPs have zero global optimal value. We reformulate the NLPs as DC Programs (DCP) which can be efficiently solved by DCA (DC Algorithm). Some preliminary numerical results illustrate the good performance of the proposed methods.