Fundamentals.- Aggregate subgradient methods for unconstrained convex minimization.- Methods with subgradient locality measures for minimizing nonconvex functions.- Methods with subgradient deletion rules for unconstrained nonconvex minimization.- Feasible point methods for convex constrained minimization problems.- Methods of feasible directions for nonconvex constrained problems.- Bundle methods.- Numerical examples.
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Für höhere Schule und Studium
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Höhe: 235 mm
Breite: 155 mm
Dicke: 21 mm
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ISBN-13
978-3-540-15642-0 (9783540156420)
DOI
Schweitzer Klassifikation
Fundamentals.- Aggregate subgradient methods for unconstrained convex minimization.- Methods with subgradient locality measures for minimizing nonconvex functions.- Methods with subgradient deletion rules for unconstrained nonconvex minimization.- Feasible point methods for convex constrained minimization problems.- Methods of feasible directions for nonconvex constrained problems.- Bundle methods.- Numerical examples.
