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dc.contributor.authorEl-Alem, Mahmoud
El-Sobky, Bothina
dc.date.accessioned 2018-06-18T17:44:06Z
dc.date.available 2018-06-18T17:44:06Z
dc.date.issued 1997-10
dc.identifier.citation El-Alem, Mahmoud and El-Sobky, Bothina. "A New Trust-Region Algorithm for General Nonlinear Programming." (1997) https://hdl.handle.net/1911/101894.
dc.identifier.urihttps://hdl.handle.net/1911/101894
dc.description.abstract A new trust-region algorithm for solving the general nonlinear programming problem is introduced. In this algorithm, an active set strategy is used together with a projected Hessian technique to convert the computation of the trial step to two easy trust-region subproblems similar to those for the unconstrained case. To force global convergence, the augmented Lagrangian for general nonlinear programming is used as a merit function. A convergence theory for this algorithm is presented. Under reasonable assumptions, it is shown that the algorithm is globally convergent. Numerical experiment on the algorithm is presented. The performance of the algorithm is reported. The numerical results show that our approach is of value and merits further investigation.
dc.format.extent 27 pp
dc.title A New Trust-Region Algorithm for General Nonlinear Programming
dc.type Technical report
dc.date.note October 1997
dc.identifier.digital TR97-25
dc.type.dcmi Text


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