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

dc.contributor.author	Tits, A.L.	en_US
dc.contributor.author	Urban, T.J.	en_US
dc.contributor.author	Bakhtiari, Sasan	en_US
dc.contributor.author	Lawrence, Craig T.	en_US
dc.contributor.department	ISR	en_US
dc.date.accessioned	2007-05-23T10:10:33Z
dc.date.available	2007-05-23T10:10:33Z
dc.date.issued	2001	en_US
dc.description.abstract	A 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.extent	357547 bytes
dc.format.mimetype	application/pdf
dc.identifier.uri	http://hdl.handle.net/1903/6192
dc.language.iso	en_US	en_US
dc.relation.ispartofseries	ISR; TR 2001-3	en_US
dc.subject	Sensor-Actuator Networks	en_US
dc.title	A Primal-Dual Interior-Point Method for Nonlinear Programming with Strong Global and Local Convergence Properties	en_US
dc.type	Technical Report	en_US

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