On Lagrangian Duality in Vector Optimization. Applications to the linear case.

Abstract

The paper deals with vector constrained extremum problems. A separation scheme is recalled; starting from it, a vector Lagrangian duality theory is developed. The linear duality due to Isermann can be embedded in this separation approach. Some classical applications are extended to the multiobjective framework in the linear case, exploiting the duality theory of Isermann.Vector Optimization, Separation, Image Space Analysis, Lagrangian Duality, Set-Valued Function.