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A Superlinearly Convergent Method of Feasible Directions for Optimization Problems Arising in the Design of Engineering Systems.

dc.contributor.authorPanier, E.R.en_US
dc.contributor.authorTits, A.L.en_US
dc.date.accessioned2007-05-23T09:34:27Z
dc.date.available2007-05-23T09:34:27Z
dc.date.issued1985en_US
dc.identifier.urihttp://hdl.handle.net/1903/4410
dc.description.abstractOptimization problems arising from engineering design problems often involve the solution of one or several constrained minimax optimization problems. It is sometimes crucial that all iterates constructed when solving such problems satisfy a given set of 'hard' inequality constraints, and generally desirable that the (maximum) objective function value improve at each iteration. In this paper, we propose an algorithm of the sequential quadratic programming (SQP) type that enjoys such properties. This algorithm is inspired from an algorithm recently proposed for the solution of single objective constrained optimization problems. Preliminary numerical results are very promising.en_US
dc.format.extent434696 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen_USen_US
dc.relation.ispartofseriesISR; TR 1985-37en_US
dc.titleA Superlinearly Convergent Method of Feasible Directions for Optimization Problems Arising in the Design of Engineering Systems.en_US
dc.typeTechnical Reporten_US
dc.contributor.departmentISRen_US


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