Monotone Variable–Metric Algorithm for Linearly Constrained Nonlinear Programming
G. Pacelli and
Maria Recchioni
Additional contact information
G. Pacelli: University of Ancona
Journal of Optimization Theory and Applications, 2000, vol. 104, issue 2, No 1, 255-279
Abstract:
Abstract A new method for linearly constrained nonlinear programming is proposed. This method follows affine scaling paths defined by systems of ordinary differential equations and it is fully parallelizable. The convergence of the method is proved for a nondegenerate problem with pseudoconvex objective function. In practice, the algorithm works also under more general assumptions on the objective function. Numerical results obtained with this computational method on several test problems are shown.
Keywords: nonlinear programming; path-following methods; differential equations; projective algorithms (search for similar items in EconPapers)
Date: 2000
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://link.springer.com/10.1023/A:1004645328197 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:joptap:v:104:y:2000:i:2:d:10.1023_a:1004645328197
Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10957/PS2
DOI: 10.1023/A:1004645328197
Access Statistics for this article
Journal of Optimization Theory and Applications is currently edited by Franco Giannessi and David G. Hull
More articles in Journal of Optimization Theory and Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().