Abstract
In this paper, an approximate smoothing approach to the non-differentiable exact penalty function is proposed for the constrained optimization problem. A simple smoothed penalty algorithm is given, and its convergence is discussed. A practical algorithm to compute approximate optimal solution is given as well as computational experiments to demonstrate its efficiency.
Highlights
Many problems in industry design, management science and economics can be modeled as the following constrained optimization problem: (P)
The penalty function methods based on various penalty functions have been proposed to solve problem (P) in the literatures
In Xu et al [9] and Lian [10], smoothing penalty functions are proposed for nonlinear inequality constrained optimization problems
Summary
School of Mathematics and Statistics, Shandong University of Technology, Shandong, China How to cite this paper: Liu, B.Z. (2019) A Smoothing Penalty Function Method for the Constrained Optimization Problem. Open Journal of Optimization, 8, 113-126 https://doi.org/10.4236/ojop.2019.84010
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