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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.
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.
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