Efficiency in terms of Lagrangian.
Bebu, I., Ureche, G. (2001)
APPS. Applied Sciences
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Bebu, I., Ureche, G. (2001)
APPS. Applied Sciences
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Christian Grossmann (2010)
Discussiones Mathematicae, Differential Inclusions, Control and Optimization
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Penalty methods, augmented Lagrangian methods and Nitsche mortaring are well known numerical methods among the specialists in the related areas optimization and finite elements, respectively, but common aspects are rarely available. The aim of the present paper is to describe these methods from a unifying optimization perspective and to highlight some common features of them.
Gutiérrez, J.M. (1997)
Journal of Convex Analysis
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Song Wen
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CONTENTSIntroduction...........................................................................................................51. Preliminaries on convex and set-valued analysis..............................................6 1.1. Convexity of sets...........................................................................................6 1.2. Convexity of set-valued mappings.................................................................9 1.3. Closed convex processes and invex set-valued...
Letizia Pellegrini (2004)
RAIRO - Operations Research - Recherche Opérationnelle
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In this paper we present the image space analysis, based on a general separation scheme, with the aim of studying lagrangian duality and shadow prices in Vector Optimization. Two particular kinds of separation are considered; in the linear case, each of them is applied to the study of sensitivity analysis, and it is proved that the derivatives of the perturbation function can be expressed in terms of vector Lagrange multipliers or shadow prices.
Giorgio Giorgi, Bienvenido Jiménez, Vincente Novo (2010)
RAIRO - Operations Research
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We consider a multiobjective optimization problem with a feasible set defined by inequality and equality constraints such that all functions are, at least, Dini differentiable (in some cases, Hadamard differentiable and sometimes, quasiconvex). Several constraint qualifications are given in such a way that generalize both the qualifications introduced by Maeda and the classical ones, when the functions are differentiable. The relationships between them are analyzed. Finally, we give...