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...

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Veröffentlicht in:Computational optimization and applications Jg. 35; H. 3; S. 375 - 398
Hauptverfasser: Meng, Zhiqing, Dang, Chuangyin, Yang, Xiaoqi
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Springer Nature B.V 01.11.2006
Schlagworte:
Algorithms
Lagrange multiplier
Methods
Optimization
Optimization techniques
Studies
ISSN:0926-6003, 1573-2894
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Zusammenfassung: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.
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ISSN:0926-6003
1573-2894
DOI:10.1007/s10589-006-8720-6