An interior point algorithm for large scale nonlinear programming

An interior point algorithm for large scale nonlinear programming (1999)

by Richard H. Byrd , Mary E. Hribar Y , Jorge Nocedal Z

Venue:	SIAM Journal on Optimization
Citations:	62 - 16 self

Datum	Value	Source
TITLE	An interior point algorithm for large scale nonlinear programming	INFERENCE
AUTHOR NAME	Richard H. Byrd	SVM HeaderParse 0.2
AUTHOR NAME	Mary E. Hribar Y	SVM HeaderParse 0.2
AUTHOR NAME	Jorge Nocedal Z	SVM HeaderParse 0.2
AUTHOR AFFIL	; Computer Science Department, University of Colorado; y; CAAM Department, Rice University, Houston TX 77005. This author was supported by Department of; Energy grant DE-FG02-87ER25047-A004.; z; ECE Department, Northwestern University, Evanston Il 60208;	SVM HeaderParse 0.2
AUTHOR ADDR	; Boulder CO 80309. This author was supported; This author was supported by National	SVM HeaderParse 0.2
ABSTRACT	The design and implementation of a new algorithm for solving large nonlinear programming problems is described. It follows a barrier approach that employs sequential quadratic programming and trust regions to solve the subproblems occurring in the iteration. Both primal and primal-dual versions of the algorithm are developed, and their performance is illustrated in a set of numerical tests. Key words: constrained optimization, interior point method, large-scale optimization, nonlinear programming, primal method, primal-dual method, successive quadratic programming, trust region method.	SVM HeaderParse 0.2
YEAR	1999	INFERENCE
VENUE	SIAM Journal on Optimization	INFERENCE
VENUE TYPE	JOURNAL	INFERENCE
CITATIONS	26 found	ParsCit 1.0