Ontology type: schema:ScholarlyArticle
2019-03-12
AUTHORSM. D. Sánchez, M. L. Schuverdt
ABSTRACTThe purpose of the present paper is to study the global convergence of a practical Augmented Lagrangian model algorithm that considers non-quadratic Penalty–Lagrangian functions. We analyze the convergence of the model algorithm to points that satisfy the Karush–Kuhn–Tucker conditions and also the weak second-order necessary optimality condition. The generation scheme of the Penalty–Lagrangian functions includes the exponential penalty function and the logarithmic-barrier without using convex information. More... »
PAGES1-19
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