On the Smoothing of the Square-Root Exact Penalty Function for Inequality Constrained Optimization

In this paper we propose two methods for smoothing a nonsmooth square-root exact penalty function for inequality constrained optimization. Error estimations are obtained among the optimal objective function values of the smoothed penalty problem, of the nonsmooth penalty problem and of the original...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Computational optimization and applications Ročník 35; číslo 3; s. 375 - 398
Hlavní autori: Meng, Zhiqing, Dang, Chuangyin, Yang, Xiaoqi
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York Springer Nature B.V 01.11.2006
Predmet:
Algorithms
Lagrange multiplier
Methods
Optimization
Optimization techniques
Studies
ISSN:0926-6003, 1573-2894
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:In this paper we propose two methods for smoothing a nonsmooth square-root exact penalty function for inequality constrained optimization. Error estimations are obtained among the optimal objective function values of the smoothed penalty problem, of the nonsmooth penalty problem and of the original optimization problem. We develop an algorithm for solving the optimization problem based on the smoothed penalty function and prove the convergence of the algorithm. The efficiency of the smoothed penalty function is illustrated with some numerical examples, which show that the algorithm seems efficient.
Bibliografia:SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ObjectType-Article-2
content type line 23
ISSN:0926-6003
1573-2894
DOI:10.1007/s10589-006-8720-6