New Exact Penalty Functions for Nonlinear Constrained Optimization Problems

For two kinds of nonlinear constrained optimization problems, we propose two simple penalty functions, respectively, by augmenting the dimension of the primal problem with a variable that controls the weight of the penalty terms. Both of the penalty functions enjoy improved smoothness. Under mild co...

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Main Authors: Bingzhuang Liu, Wenling Zhao
Format: Article
Language:English
Published: Wiley 2014-01-01
Series:Abstract and Applied Analysis
Online Access:http://dx.doi.org/10.1155/2014/738926
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author Bingzhuang Liu
Wenling Zhao
author_facet Bingzhuang Liu
Wenling Zhao
author_sort Bingzhuang Liu
collection DOAJ
description For two kinds of nonlinear constrained optimization problems, we propose two simple penalty functions, respectively, by augmenting the dimension of the primal problem with a variable that controls the weight of the penalty terms. Both of the penalty functions enjoy improved smoothness. Under mild conditions, it can be proved that our penalty functions are both exact in the sense that local minimizers of the associated penalty problem are precisely the local minimizers of the original constrained problem.
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publishDate 2014-01-01
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spelling doaj-art-2f4cf197c3eb4d7c88eafaeef4d7ea152025-08-20T03:55:16ZengWileyAbstract and Applied Analysis1085-33751687-04092014-01-01201410.1155/2014/738926738926New Exact Penalty Functions for Nonlinear Constrained Optimization ProblemsBingzhuang Liu0Wenling Zhao1School of Science, Shandong University of Technology, Zibo, Shandong 255049, ChinaSchool of Science, Shandong University of Technology, Zibo, Shandong 255049, ChinaFor two kinds of nonlinear constrained optimization problems, we propose two simple penalty functions, respectively, by augmenting the dimension of the primal problem with a variable that controls the weight of the penalty terms. Both of the penalty functions enjoy improved smoothness. Under mild conditions, it can be proved that our penalty functions are both exact in the sense that local minimizers of the associated penalty problem are precisely the local minimizers of the original constrained problem.http://dx.doi.org/10.1155/2014/738926
spellingShingle Bingzhuang Liu
Wenling Zhao
New Exact Penalty Functions for Nonlinear Constrained Optimization Problems
Abstract and Applied Analysis
title New Exact Penalty Functions for Nonlinear Constrained Optimization Problems
title_full New Exact Penalty Functions for Nonlinear Constrained Optimization Problems
title_fullStr New Exact Penalty Functions for Nonlinear Constrained Optimization Problems
title_full_unstemmed New Exact Penalty Functions for Nonlinear Constrained Optimization Problems
title_short New Exact Penalty Functions for Nonlinear Constrained Optimization Problems
title_sort new exact penalty functions for nonlinear constrained optimization problems
url http://dx.doi.org/10.1155/2014/738926
work_keys_str_mv AT bingzhuangliu newexactpenaltyfunctionsfornonlinearconstrainedoptimizationproblems
AT wenlingzhao newexactpenaltyfunctionsfornonlinearconstrainedoptimizationproblems