Difference of convex functions optimization algorithms (DCA) for globally minimizing nonconvex quadratic forms on Euclidean balls and spheres

Authors:
Pham Dinh Tao;Le Thi Hoai An
Affiliations:
Mathematical Modelling and Applied Optimization Group, LMI-INSA Rouen, CNRS URA 1378, BP 08, 76131 Mont Saint Aignan, France;Mathematical Modelling and Applied Optimization Group, LMI-INSA Rouen, CNRS URA 1378, BP 08, 76131 Mont Saint Aignan, France
Venue:
Operations Research Letters
Year:
1996

Citing 1
Cited 3

Practical methods of optimization; (2nd ed.)

Practical methods of optimization; (2nd ed.)

Solving a Class of Linearly Constrained Indefinite QuadraticProblems by D.C. Algorithms

Journal of Global Optimization
Conditions for Global Optimality 2

Journal of Global Optimization
Behavior of DCA sequences for solving the trust-region subproblem

Journal of Global Optimization

Quantified Score

Hi-index	0.00

Visualization

Abstract

We present DCA for globally minimizing quadratic forms on Euclidean balls and spheres. Since these problems admit at most one local-nonglobal minimizer, DCA converges in general to a solution for these problems. Numerical simulations show robustness, stability and efficiency of DCA with respect to related standard methods.