An experimental investigation of enumerative methods for the linear complementarity problem
Computers and Operations Research
New branch-and-bound rules for linear bilevel programming
SIAM Journal on Scientific and Statistical Computing
A sequential LCP method for bilevel linear programming
Annals of Operations Research - Special issue on hierarchical optimization
Matrix computations (3rd ed.)
Computational Optimization and Applications
Global optimization of mixed-integer nonlinear programs: A theoretical and computational study
Mathematical Programming: Series A and B
A two-sided relaxation scheme for Mathematical Programs with Equilibrium Constraints
SIAM Journal on Optimization
Interior Methods for Mathematical Programs with Complementarity Constraints
SIAM Journal on Optimization
The eigenvalue complementarity problem
Computational Optimization and Applications
A finite branch-and-bound algorithm for nonconvex quadratic programming via semidefinite relaxations
Mathematical Programming: Series A and B
On the Global Solution of Linear Programs with Linear Complementarity Constraints
SIAM Journal on Optimization
Local minima of quadratic forms on convex cones
Journal of Global Optimization
The eigenvalue complementarity problem
Computational Optimization and Applications
Optimization Methods & Software - GLOBAL OPTIMIZATION
Cone-constrained eigenvalue problems: theory and algorithms
Computational Optimization and Applications
Reconstructing a matrix from a partial sampling of Pareto eigenvalues
Computational Optimization and Applications
A DC programming approach for solving the symmetric Eigenvalue Complementarity Problem
Computational Optimization and Applications
A new method for solving Pareto eigenvalue complementarity problems
Computational Optimization and Applications
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In this paper, we discuss the eigenvalue complementarity problem (EiCP) where at least one of its defining matrices is asymmetric. A sufficient condition for the existence of a solution to the EiCP is established. The EiCP is shown to be equivalent to finding a global minimum of an appropriate merit function on a convex set Ω defined by linear constraints. A sufficient condition for a stationary point of this function on Ω to be a solution of the EiCP is presented. A branch-and-bound procedure is developed for finding a global minimum of this merit function on Ω. In addition, a sequential enumerative algorithm for the computation of the minimum and the maximum eigenvalues is also discussed. Computational experience is included to highlight the efficiency and efficacy of the proposed methodologies to solve the asymmetric EiCP.