Solving linear programming using Newton method and Goldstein conditions

Basit Öğe Kaydı
dc.contributor.authorKhosravi, P.
dc.contributor.authorNavidi, H.
dc.contributor.authorMalek, A.
dc.date.accessioned2024-07-12T20:51:08Z
dc.date.available2024-07-12T20:51:08Z
dc.date.issued2009en_US
dc.departmentFakülteler, İnsan ve Toplum Bilimleri Fakültesi, Matematik Bölümüen_US
dc.description.abstractThe aim of this paper is to find an exact least 2-norm solution to the dual linear programming problem and to generate an exact solution to the primal programming problem. The Newton method is proposed for solving linear programs with very large numbers of constraints and variables. We use Goldstein conditions in order to find a suitable step-size in each iteration. The proposed method is based on the apparently overlooked fact that the dual of an exterior penalty formulation of a linear program provides an exact least 2-norm solution to the dual of the linear program. Solving the dual yields an exact least 2-norm solution to the dual and the exact least 2-norm solution to dual problem can be used to generate an exact primal solution. A simple prototype of the method is given in eleven lines of MATLAB code. Encouraging computational results are presented.en_US
dc.identifier.citationKhosravi, P., Navidi, H. ve Malek, A. (2009). Solving linear programming using Newton method and Goldstein conditions. Maltepe Üniversitesi. s. 319.en_US
dc.identifier.endpage320en_US
dc.identifier.isbn9.78605E+12
dc.identifier.startpage319en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12415/2353
dc.language.isoenen_US
dc.publisherMaltepe Üniversitesien_US
dc.relation.ispartofInternational Conference of Mathematical Sciencesen_US
dc.relation.publicationcategoryUluslararası Konferans Öğesi - Başka Kurum Yazarıen_US
dc.rightsCC0 1.0 Universal*
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/*
dc.snmzKY07718
dc.titleSolving linear programming using Newton method and Goldstein conditionsen_US
dc.typeConference Object
dspace.entity.typePublication

Dosyalar

Koleksiyon

İnsan ve Toplum Bilimleri Fakültesi Koleksiyonu