Lagrangean decomposition for integer programming : theory and applications
Monique Guignard, Siwhan Kim (1987)
RAIRO - Operations Research - Recherche Opérationnelle
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Displaying similar documents to “Centralization and decentralization of decision making. The decomposition of any linear programme in primal and dual directions – to obtain a primal and a dual master solved in parallel and one or more common subproblems”
Lagrangean decomposition for integer programming : theory and applications
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RAIRO - Operations Research - Recherche Opérationnelle
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Letizia Pellegrini (1998)
RAIRO - Operations Research - Recherche Opérationnelle
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P F. Körner (1991)
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On Finite Termination in the Primal-Dual Method for Linear Programming
Nebojša V. Stojković (2001)
The Yugoslav Journal of Operations Research
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Linear programming with inequality constraints via entropic perturbation.
Tsao, H.-S.Jacob, Fang, Shu-Cherng (1996)
International Journal of Mathematics and Mathematical Sciences
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Duality theorems for a class of non-linear programming problems.
Shyam S. Chadha (1988)
Trabajos de Investigación Operativa
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Duality of linear programming is used to establish an important duality theorem for a class of non-linear programming problems. Primal problem has quasimonotonic objective function and a convex polyhedron as its constraint set.
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Popescu, Elena (2003)
Analele Ştiinţifice ale Universităţii “Ovidius" Constanţa. Seria: Matematică
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Duality of transformation functions in the interior point methods.
Halická, M., Hamala, M. (1996)
Acta Mathematica Universitatis Comenianae. New Series
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J. Gondzio, D. Tachat (1994)
RAIRO - Operations Research - Recherche Opérationnelle
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On dual vector optimization and shadow prices
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.