The year 2015 marks the 30th birthday of DC (Difference of Convex functions) programming
and DCA (DC Algorithms) which constitute the backbone of nonconvex programming and …

In this paper, we consider the tensor generalized eigenvalue complementarity problem
(TGEiCP), which is an interesting generalization of matrix eigenvalue complementarity …

In this paper, we study the Eigenvalue Complementarity Problem (EiCP) when its matrix A
belongs to the class S (G)={A=[aij]: aij= aji≠ 0 iff ij∈ E}, where G=(V, E) is a connected …

This paper studies tensor eigenvalue complementarity problems. Basic properties of
standard and complementarity tensor eigenvalues are discussed. We formulate tensor …

In this paper, we investigate a DC (Difference of Convex functions) programming technique
for solving large scale Eigenvalue Complementarity Problems (EiCP) with real symmetric …

In this paper, we introduce a new method, called the Lattice Projection Method (LPM), for
solving eigenvalue complementarity problems. The original problem is reformulated to find …

In this paper, we propose nonlinear programming (NLP) formulations and difference of
convex functions (DC) programming approaches for the asymmetric eigenvalue …

In this paper, we study numerical methods for solving eigenvalue complementarity problems
involving the product of second-order cones (or Lorentz cones). We reformulate such …

In this paper, we introduce a unified framework of Tensor Higher-Degree Eigenvalue
Complementarity Problem (THDEiCP), which goes beyond the framework of the typical …

Abstract We provide Completely Positive and Copositive Optimization formulations for the
Constrained Fractional Quadratic Problem (CFQP) and Standard Fractional Quadratic …