Solving constraint optimization problems using the penalty and augmented Lagrangian methods Resolución de los problemas de optimización con restricciones mediante los métodos de penalización y del Lagrangiano aumentado

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Manuel Vázquez Mourazos

Abstract

In solving constrained optimization problems (also by the name of mathematical programming), a variety of algorithms can be established. As the research in this field is very extensive, new and increasingly sophisticated methods are continually being developed to solve this type of problem.


 


In this article the methods of penalization will be presented. These are the most intuitive and allow to show an introduction within the resolution of this type of problem. Their properties will be studied, and then their deduction, interpretation and demonstration of their convergence will proceed. Finally, the augmented Lagrangian method will be presented. This is a method that improves on the previous ones and allows for greater and better convergence. Likewise, this article supposes an introduction to the optimization algorithms of constraint optimization, showing an introduction to the numerical methods used in mathematical programming.

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How to Cite
Vázquez Mourazos, M. (2021). Solving constraint optimization problems using the penalty and augmented Lagrangian methods: Resolución de los problemas de optimización con restricciones mediante los métodos de penalización y del Lagrangiano aumentado. Revista Digital: Matemática, Educación E Internet, 21(2). https://doi.org/10.18845/rdmei.v21i2.5605
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