Abstract
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.
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Coleman, T.F., Liu, J. & Yuan, W. A Quasi-Newton Quadratic Penalty Method for Minimization Subject to Nonlinear Equality Constraints. Computational Optimization and Applications 15, 103–123 (2000). https://doi.org/10.1023/A:1008730909894
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DOI: https://doi.org/10.1023/A:1008730909894