Accession Number : ADA115667
Title : On the Convergence of a Sequential Quadratic Programming Method with an Augmented Lagrangian Line Search Functions.
Descriptive Note : Technical rept.,
Corporate Author : STANFORD UNIV CA SYSTEMS OPTIMIZATION LAB
Personal Author(s) : Schittkowski,Klaus
PDF Url : ADA115667
Report Date : Jan 1982
Pagination or Media Count : 26
Abstract : Sequential quadratic programming methods as developed by Wilson, Han, and Powell have gained considerable attention in the last few years mainly because of their outstanding numerical performance. Although the theoretical convergence aspects of this method and its various modifications have been investigated in the literature, there still remain some open questions which will be treated in this paper. The convergence theory to be presented, takes into account the additional variable introduced in the quadratic programming subproblem to avoid inconsistency, the one-dimensional minimization procedure, and, in particular, and 'active set' strategy to avoid the recalculation of unnecessary gradients. This paper also contains a detailed mathematical description of a nonlinear programming algorithm which has been implemented by the author.
Descriptors : *Quadratic programming, *Convergence, *Sequences(Mathematics), Lagrangian functions, Optimization, Searching, Nonlinear programming, Algorithms, One dimensional
Subject Categories : Theoretical Mathematics
Distribution Statement : APPROVED FOR PUBLIC RELEASE