October  2005, 1(4): 533-547. doi: 10.3934/jimo.2005.1.533

Quadratic smoothing approximation to $l_1$ exact penalty function in global optimization

1. 

School of Mathematics and Computer Science, Chongqing Normal University, Chongqing 400047, China

2. 

Department of Applied Mathematics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong, China

3. 

School of Mathematical Sciences, Fudan University, Shanghai 200433, China

4. 

Department of Mathematics, Shanghai University, Shanghai 200444, China

Received  May 2004 Revised  December 2004 Published  October 2005

In this paper, a new quadratic smoothing approximation to the $l_1$ exact penalty function is proposed. It is shown that under certain conditions, if there exists a global minimizer of the original constrained optimization problem in the ''interior'' of the feasible set of the original constrained optimization problem, then any global minimizer of the smoothed penalty problem is a global minimizer of the original constrained optimization problem when the penalty parameter is sufficiently large; and if the feasible region of the original constrained optimization problem is ''robust'', then any global minimizer of the smoothed penalty problem is a feasible approximate global minimizer of the original constrained optimization problem when the penalty parameter is sufficiently large, and the precision of the approximation can be set in advance. Some numerical examples are given to illustrate that constrained optimization problems can be well solved by the present smoothing scheme.
Citation: Z.Y. Wu, H.W.J. Lee, F.S. Bai, L.S. Zhang. Quadratic smoothing approximation to $l_1$ exact penalty function in global optimization. Journal of Industrial & Management Optimization, 2005, 1 (4) : 533-547. doi: 10.3934/jimo.2005.1.533
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