An Interior Point Algorithm for the General Nonlinear Programming Problem with Trust Region Globalization

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dc.contributor.authorDas, Indraneelen_US
dc.date.accessioned2018-06-18T17:42:59Zen_US
dc.date.available2018-06-18T17:42:59Zen_US
dc.date.issued1996-07en_US
dc.date.noteJuly 1996en_US
dc.description.abstractThis paper attempts to develop an SQP-based interior point technique for solving the general nonlinear programming problem using trust region globalization and the Coleman-Li scaling. The SQP subproblem is decomposed into a normal and a reduced tangential subproblem in the tradition of numerous works on equality constrained optimization, and strict feasibility is maintained with respect to the bounds. This is intended to be an extension of previous work by Coleman & Li and Vicente. Even though no theoretical proofs of convergence are provided, some computational results are presented which indicate that this algorithm holds promise. The computational experiments have been geared towards improving the semi-local convergence of the algorithm; in particular high sensitivity of the speed of convergence with respect to the fraction of the trust region radius allowed for the normal step and with respect to the initial trust region radius are observed. The chief advantages of this algorithm over primal-dual interior point algorithms are better handling of the `sticking problem' and a reduction in the number of variables by elimination of the multipliers of bound constraints.en_US
dc.format.extent32 ppen_US
dc.identifier.citationDas, Indraneel. "An Interior Point Algorithm for the General Nonlinear Programming Problem with Trust Region Globalization." (1996) <a href="https://hdl.handle.net/1911/101879">https://hdl.handle.net/1911/101879</a>.en_US
dc.identifier.digitalTR96-17en_US
dc.identifier.urihttps://hdl.handle.net/1911/101879en_US
dc.language.isoengen_US
dc.titleAn Interior Point Algorithm for the General Nonlinear Programming Problem with Trust Region Globalizationen_US
dc.typeTechnical reporten_US
dc.type.dcmiTexten_US
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