Abstract
In this paper, we use the Lagrange multipliers approach to study a general infinite-dimensionalinequality-constrained linear program IP. The main problem we are concerned with is to show that thestrong duality condition for IP holds, so that IP and its dual IP* are both solvable and their optimal values coincide. To do this, we first express IP as a convex program with a Lagrangian function L, say. Then we show that the strong duality condition implies the existence of a saddle point for L, and that, under an additional, mild condition, theconverse is also true. Moreover, the saddle point gives optimal solutions for IP and IP*. Thus, our original problem is essentially reduced to prove the existence of a saddle point for L, which is shown to be the case under suitable assumptions. We use this fact to studyequality-constrained programs, and we illustrate our main results with applications to thegeneral capacity and themass transfer problems.
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This research was partially supported by the Consejo Nacional de Ciencia y Tecnología (CONACYT) grants 32299-E and 37355-E. It was also supported by CONACYT (for JRG and RRLM) and PROMEP (for JRG) scholarships.
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Gabriel, J.R., López-Martínez, R.R. & Hernández-Lerma, O. The lagrange approach to infinite linear programs. Top 9, 293–314 (2001). https://doi.org/10.1007/BF02579088
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DOI: https://doi.org/10.1007/BF02579088