A Quasi-Newton Quadratic Penalty Method for Minimization Subject to Nonlinear Equality Constraints

We present a modified quadratic penalty function method for equality constrained optimization problems. The pivotal feature of our algorithm is that at every iterate we invoke a special change of variables to improve the ability of the algorithm to follow the constraint level sets. This change of va...

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Bibliographic Details
Published inComputational optimization and applications Vol. 15; no. 2; pp. 103 - 123
Main Authors Coleman, Thomas F., Liu, Jianguo, Yuan, Wei
Format Journal Article
LanguageEnglish
Published New York Springer Nature B.V 01.02.2000
Subjects
Algorithms
Applied mathematics
Approximation
Computational mathematics
Mathematical models
Methods
Neighborhoods
Nonlinear programming
Optimization
Studies
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ISSN0926-6003
1573-2894
DOI10.1023/A:1008730909894

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Summary:We present a modified quadratic penalty function method for equality constrained optimization problems. The pivotal feature of our algorithm is that at every iterate we invoke a special change of variables to improve the ability of the algorithm to follow the constraint level sets. This change of variables gives rise to a suitable block diagonal approximation to the Hessian which is then used to construct a quasi-Newton method. We show that the complete algorithm is globally convergent. Preliminary computational results are reported.[PUBLICATION ABSTRACT]
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ISSN:0926-6003
1573-2894
DOI:10.1023/A:1008730909894