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Methods of descent for nondifferentiable optimization. (English) Zbl 0561.90059
Lecture Notes in Mathematics. 1133. Berlin etc.: Springer-Verlag. VI, 362 p. DM 51.50 (1985).
This book deals with numerical methods for nondifferentiable (or nonsmooth) optimization. It intends to give an overview on methods of descent for minimizing nonsmooth functions. The functions involved in the data of the problem are locally Lipschitz (or belonging to large subclasses of Locally Lipschitz functions) but not necessarily \(C^ 1\) or convex.
Contents. Chapter 1: Fundamentals; Chapter 2: Aggregate subgradient methods for unconstrained convex minimization; Chapter 3: Methods with subgradient locality measures for minimizing nonconvex functions; Chapter 4: Methods with subgradient delation rules for unconstrained nonconvex minimization; Chapter 5: Feasible point methods for convex constrained minimization problems; Chapter 6: Methods of feasible directions for nonconvex constrained problems; Chapter 7: Bundle methods; Chapter 8: Numerical examples.

MSC:
90C30 Nonlinear programming
49M37 Numerical methods based on nonlinear programming
65K05 Numerical mathematical programming methods
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