Decrease of the Penalty Parameter in Differentiable Penalty Function Methods

Roohollah Aliakbari Shandiz, Emran Tohidi

Faculty of Mathematical Sciences, Sharif University of Technology, Tehran, Iran.
Ferdowsi University of Mashhad, Mashhad, Iran.

DOI: 10.4236/tel.[phone]                

Abstract

We propose a simple modification to the differentiable penalty methods for solving nonlinear programming problems. This modification decreases the penalty parameter and the ill-conditioning of the penalty method and leads to a faster convergence to the optimal solution. We extend the modification to the augmented Lagrangian method and report some numerical results on several nonlinear programming test problems, showing the effectiveness of the proposed approach.

Keywords

Nonlinear Programming, Penalty Method, Penalty Parameter, Differentiable Penalty Methods

Conflicts of Interest

The authors declare no conflicts of interest.

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