ISSN:
1573-2894
Keywords:
nonlinearly constrained optimization
;
equality constraints
;
quasi-Newton methods
;
BFGS
;
quadratic penalty function
;
reduced Hessian approximation
Source:
Springer Online Journal Archives 1860-2000
Topics:
Computer Science
Notes:
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.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1023/A:1008730909894
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