Titlebook: Nonlinear Optimization and Related Topics; Gianni Di Pillo,Franco Giannessi Book 2000 Springer Science+Business Media Dordrecht 2000 algor

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A truncated Newton method for constrained optimization,. To this aim, we first consider a primal-dual system of nonlinear equations .(.) = 0 with the property that .(.) = 0 ? (.) is a . for the constrained problem. This system is derived on the basis of an efficient strategy for the identification of the constraints active at the solution. Then, we adop

Contracture

mendacity

Iterative methods for ill-conditioned linear systems from optimization,onlinear minimization. The preconditioners are chosen so as to isolate the dominant cause of ill conditioning. The methods are stablized using a restricted form of iterative refinement. Numerical results illustrate the approaches considered.

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詳細(xì)目錄

Generic Existence, Uniqueness and Stability in Optimization Problems,oblems of convex and quasi-convex programming with inequality constraints have these properties on the class of data consisting of continuous convex (resp. quasi-convex and bounded below on bounded sets) functions with the topology of uniform convergence on bounded sets. On the other hand, it is sho

Neonatal

Functions with Primal-Dual Gradient Structure and ,-Hessians,ins finitely defined maximum value functions and maximum eigenvalue functions as well as other infinitely determined max-functions. For such a function there is a space decomposition that allows us to identify a subspace u on which the function appears smooth. Moreover, the special structure combine

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Misgiving

A new merit function and an SQP method for non-strictly monotone variational inequalities,y problems have in common that they include a penalty function for the explicit constraints, the value of the penalty parameter for which is subject to the requirement of being large enough compared to estimates of the optimal Lagrange multipliers. In existing applications of the SQP algorithm to va

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A Logarithmic Barrier Approach to Fischer Function,topic in the field of mathematical programming. Various merit functions play important roles in such reformulations. In this paper, among others, we consider the well-known Fischer function and explore its relationship with other merit functions. It is shown that the Fischer function can be derived

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On an Approach to Optimization Problems with a Probabilistic Cost and or Constraints,roblems are characterized by the fact that the probability of failure of one or several components either must be minimized or must not exceed a preassigned threshold. Our approach is interactive: it consists of replacing the original optimal design problem in which either the cost function or a con