A Smoothing Objective Penalty Function Algorithm for Inequality Constrained Optimization Problems

DOI10.1080/01630563.2011.577262zbMath1227.65051OpenAlexW1989837342MaRDI QIDQ3173503

Zhiqing Meng, Rui Shen, Chuangyin Dang, Min Jiang

Publication date: 10 October 2011

Published in: Numerical Functional Analysis and Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/01630563.2011.577262

zbMATH Keywords

algorithmsmoothingexact penalty functionobjective penalty functionconstrained optimization problemsobjective parameter

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonlinear programming (90C30)

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A new smoothing approach to exact penalty functions for inequality constrained optimization problems ⋮ Exactness and algorithm of an objective penalty function ⋮ The smoothing objective penalty function method for two-cardinality sparse constrained optimization problems ⋮ An objective penalty method for optimistic bilevel programming problems ⋮ New Smoothing Approximations to Piecewise Smooth Functions and Applications ⋮ Second-Order Smoothing Objective Penalty Function for Constrained Optimization Problems ⋮ An Objective Penalty Function Algorithm for Bilevel Programming Based on Multi-Parameters ⋮ Smoothing Approximation to the New Exact Penalty Function with Two Parameters

Cites Work

• Unnamed Item
• On the smoothing of the square-root exact penalty function for inequality constrained optimization
• A Boolean penalty method for zero-one nonlinear programming
• An objective penalty function method for nonlinear programming.
• Scheduling with monotonous earliness and tardiness penalties
• A penalty function algorithm with objective parameters for nonlinear mathematical programming
• Exact penalty functions in nonlinear programming
• An Exact Penalization Viewpoint of Constrained Optimization
• On Smoothing Exact Penalty Functions for Convex Constrained Optimization
• Smoothing Nonlinear Penalty Functions for Constrained Optimization Problems
• Globally Convergent Algorithms for Convex Programming
• Optimization by Least Squares
• Non-Linear Programming Via Penalty Functions