Smoothing approximation to the square-order exact penalty functions for constrained optimization
type: Item
instance of: scholarly article
title: Smoothing approximation to the square-order exact penalty functions for constrained optimization
zbMATH Open document ID: 1397.65096
DOI: 10.1155/2013/568316
author: Shu-Jun Lian
author: Jinli Han
published in: Journal of Applied Mathematics
publication date: 2018-10-10T00:00:00Z
review text: Summary: A method is proposed to smooth the square-order exact penalty function for inequality constrained optimization. It is shown that, under some conditions, an approximately optimal solution of the original problem can be obtained by searching an approximately optimal solution of the smoothed penalty problem. An algorithm based on the smoothed penalty functions is given. The algorithm is shown to be convergent under mild conditions. Two numerical examples show that the algorithm seems efficient.
Mathematics Subject Classification ID: 65K10
zbMATH DE Number: 6950752
Wikidata QID: Q59003038
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1155/2013/568316
OpenAlex ID: W2047434255
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description: scientific article; zbMATH DE number 6950752