Next Article in Journal
Topology on Soft Continuous Function Spaces
Previous Article in Journal
Broken Bar Diagnosis for Squirrel Cage Induction Motors Using Frequency Analysis Based on MCSA and Continuous Wavelet Transform
Article Menu

Export Article

Open AccessArticle
Math. Comput. Appl. 2017, 22(2), 31;

A New Smoothing Nonlinear Penalty Function for Constrained Optimization

School of Mathematical Sciences, Dalian University of Technology, Dalian 116024, China
Department of Mathematics, Shanghai University, Shanghai 200444, China
Yen Bai Teacher’s Training College, Yen Bai City 320000, Vietnam
Department of Education and Training Yen Bai, Yen Bai City 320000, Vietnam
Author to whom correspondence should be addressed.
Academic Editor: Fazal M. Mahomed
Received: 5 November 2016 / Revised: 29 March 2017 / Accepted: 4 April 2017 / Published: 12 April 2017
Full-Text   |   PDF [777 KB, uploaded 12 April 2017]   |  


In this study, a new smoothing nonlinear penalty function for constrained optimization problems is presented. It is proved that the optimal solution of the smoothed penalty problem is an approximate optimal solution of the original problem. Based on the smoothed penalty function, we develop an algorithm for finding an optimal solution of the optimization problems with inequality constraints. We further discuss the convergence of this algorithm and test this algorithm with three numerical examples. The numerical examples show that the proposed algorithm is feasible and effective for solving some nonlinear constrained optimization problems. View Full-Text
Keywords: penalty function; smoothing method; constrained optimization penalty function; smoothing method; constrained optimization

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Yang, T.; Binh, N.T.; Thang, T.M.; Hoa, D.T. A New Smoothing Nonlinear Penalty Function for Constrained Optimization. Math. Comput. Appl. 2017, 22, 31.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Metrics

Article Access Statistics



[Return to top]
Math. Comput. Appl. EISSN 2297-8747 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top