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《《1997 An Interior Point Algorithm for Large Scale Nonlinear Programming》.pdf

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An Interior Point Algorithm for Large Scale Nonlinear Programming Richard H Byrd Mary E Hribar y Jorge No cedalz July Abstract The design and implementation of a new algorithm for solving large nonlinear pro gramming problems is describ ed It follows a barrier approach that employs sequential quadratic programming and trust regions to solve the subproblems o ccurring in the iteration Both primal and primaldual versions of the algorithm are develop ed and their p erformance is illustrated in a set of numerical tests Key words constrained optimization interior point method largescale optimization non linear programming primal method primaldual method successive quadratic program ming trust region method Computer Science Department University of Colorado Boulder CO This author was supp orted by AR O grant DAAH and AFOSR grant F y CAAM Department Rice University Houston TX This author was supp orted by Department of Energy grant DEF GERA z ECE Department Northwestern University Evanston Il This author was supp orted by National Science Foundation grant CCR and by Department of Energy grant DEF GERA Intro duction In thispaperwe discussthe design implementationandperformance of an interiorpoint method for solving the nonlinearly constrained optimization problem min f x subject to h x g x n n t n m where f R R h R R and g R R are smooth functions We are particularlyinterested in the case when is not a convex p
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