A Globally Convergent Method of Constrained Minimization by Solving Subproblems of the Conic Model

A Globally Convergent Method of Constrained Minimization by Solving Subproblems of the Conic Model

Year:    1989

Author:    Ling-Ping Sun

Journal of Computational Mathematics, Vol. 7 (1989), Iss. 3 : pp. 234–243

Abstract

A new method for nonlinearly constrained optimization problems is proposed. The method consists of two steps. In the first step, we get a search direction by the linearly constrained subproblems based on conic functions. In the second step, we use a differentiable penalty function, and regard it as the metric function of the problem. From this, a new approximate solution is obtained. The global convergence of the given method is also proved.

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/1989-JCM-9474

Journal of Computational Mathematics, Vol. 7 (1989), Iss. 3 : pp. 234–243

Published online:    1989-01

AMS Subject Headings:   

Copyright:    COPYRIGHT: © Global Science Press

Pages:    10

Keywords:   

Author Details

Ling-Ping Sun