Zobrazit minimální záznam

dc.contributor.authorToloo, Mehdi
dc.date.accessioned2021-10-06T10:29:56Z
dc.date.available2021-10-06T10:29:56Z
dc.date.issued2021
dc.identifier.citationMathematics. 2021, vol. 9, issue 14, art. no. 1586.cs
dc.identifier.issn2227-7390
dc.identifier.urihttp://hdl.handle.net/10084/145286
dc.description.abstractLinear fractional programming has been an important planning tool for the past four decades. The main contribution of this study is to show, under some assumptions, for a linear programming problem, that there are two different dual problems (one linear programming and one linear fractional functional programming) that are equivalent. In other words, we formulate a linear programming problem that is equivalent to the general linear fractional functional programming problem. These equivalent models have some interesting properties which help us to prove the related duality theorems in an easy manner. A traditional data envelopment analysis (DEA) model is taken, as an instance, to illustrate the applicability of the proposed approach.cs
dc.language.isoencs
dc.publisherMDPIcs
dc.relation.ispartofseriesMathematicscs
dc.relation.urihttps://doi.org/10.3390/math9141586cs
dc.rights© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectlinear fractional programmingcs
dc.subjectlinear programmingcs
dc.subjectdualitycs
dc.subjectdata envelopment analysis (DEA)cs
dc.titleAn equivalent linear programming form of general linear fractional programming: A duality approachcs
dc.typearticlecs
dc.identifier.doi10.3390/math9141586
dc.rights.accessopenAccesscs
dc.type.versionpublishedVersioncs
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume9cs
dc.description.issue14cs
dc.description.firstpageart. no. 1586cs
dc.identifier.wos000676762000001


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Zobrazit minimální záznam

© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.
Kromě případů, kde je uvedeno jinak, licence tohoto záznamu je © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.