A Primal-Dual Interior-Point Method for Nonlinear Programming with Strong Global and Local Convergence Properties

dc.contributor.authorTits, A.L.en_US
dc.contributor.authorUrban, T.J.en_US
dc.contributor.authorBakhtiari, Sasanen_US
dc.contributor.authorLawrence, Craig T.en_US
dc.contributor.departmentISRen_US
dc.date.accessioned2007-05-23T10:10:33Z
dc.date.available2007-05-23T10:10:33Z
dc.date.issued2001en_US
dc.description.abstractA scheme---inspired from an old idea due to Mayne and Polak (Math. Prog.,vol.~11, 1976, pp.~67--80)---is proposed for extending to general smoothconstrained optimization problems a previously proposed feasibleinterior-point method for inequality constrained problems.It is shown that the primal-dual interior point framework allows for asignificantly more effective implementation of the Mayne-Polak idea thanthat discussed an analyzed by the originators in the contextof first order methods of feasible direction. Strong global and localconvergence results are proved under mild assumptions. In particular,the proposed algorithm does not suffer the Wachter-Biegler effect.en_US
dc.format.extent357547 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttp://hdl.handle.net/1903/6192
dc.language.isoen_USen_US
dc.relation.ispartofseriesISR; TR 2001-3en_US
dc.subjectSensor-Actuator Networksen_US
dc.titleA Primal-Dual Interior-Point Method for Nonlinear Programming with Strong Global and Local Convergence Propertiesen_US
dc.typeTechnical Reporten_US

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