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

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 r...

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Veröffentlicht in:	Operations research letters Jg. 19; H. 5; S. 207 - 216
Hauptverfasser:	Tao, Pham Dinh, An, Le Thi Hoai
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier B.V 01.11.1996 Elsevier
Schlagworte:	Applied sciences Computer Science d.c. optimization d.c. optimization algorithms Exact sciences and technology Local and global optimality conditions Mathematical programming Nonconvex quadratic minimization Operational research and scientific management Operational research. Management science Optimization. Search problems d.c. optimization algorithms Local and global optimality conditions Nonconvex quadratic minimization d.c. optimization Non convex programming Algorithms Euclidean theory Optimality condition Spheres Quadratic programming Optimization
ISSN:	0167-6377, 1872-7468
Online-Zugang:	Volltext
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