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Titlebook: Recent Advances in Optimization; Proceedings of the 8 Peter Gritzmann,Reiner Horst,Rainer Tichatschke Conference proceedings 1997 Springer-

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楼主: Philanthropist
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On the Best Approximation of Set-Valued Functions, . be a finite dimensional subspace of .. The problem of the Chebyshev approximation of a function . ∈ . by functions from . can be put in the form .. ∈ V. In this paper we solve the two optimization prob-lems ..∈ V and ..∈ V, where both the functions . are upper and lower semicontinuous, respective
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A New Decomposition Method in Nonconvex Programming Via a Separable Augmented Lagrangian,erties in the neighbourhood of isolated local minima in the nonconvex case. It can be seen as a separable Augmented Lagrangian method based on the primal resource-directive decomposition scheme. Indeed, the primal allocations work as decoupling variables and each local allocation constraint is penal
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Which Fixed Point Does the Iteration Method Select?,if any) is considered. Two kinds of properties satisfied by this method that cover widely recent results on the prox or gradient-prox method for convex optimization and monotone inclusions are presented: localization and selection.
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