《《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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