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Improvement of Karush–Kuhn–Tucker conditions under uncertainties using robust decision making indexes

Abstract Almost all practical engineering problems work with uncertainties. Particularly, in chemical engineering problems, uncertainties in process models and measurements increase complexity on optimization modeling. In these cases, points are… Click to show full abstract

Abstract Almost all practical engineering problems work with uncertainties. Particularly, in chemical engineering problems, uncertainties in process models and measurements increase complexity on optimization modeling. In these cases, points are transformed in regions, and the point conditions need to be extended to its neighborhood. Extension and validation of Karush–Kuhn–Tucker (KKT) conditions under uncertainties scenarios are not trivial. In this paper, we propose two new conditions to improve robustness at second order KKT conditions.

Keywords: karush kuhn; kuhn tucker; conditions uncertainties

Journal Title: Applied Mathematical Modelling
Year Published: 2017

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