LU Decomposition in DEA with an Application to Hospitals

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F16%3A86098950" target="_blank" >RIV/61989100:27510/16:86098950 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1007/s10614-015-9501-z" target="_blank" >http://dx.doi.org/10.1007/s10614-015-9501-z</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s10614-015-9501-z" target="_blank" >10.1007/s10614-015-9501-z</a>

Result language

angličtina

Original language name

LU Decomposition in DEA with an Application to Hospitals

Original language description

A fundamental problem that usually appears in linear systems is to find a vector satisfying . This linear system is encountered in many research applications and more importantly, it is required to be solved in many contexts in applied mathematics. LU decomposition method, based on the Gaussian elimination, is particularly well suited for spars and large-scale problems. Linear programming (LP) is a mathematical method to obtain optimal solutions for a linear system that is more being considered in various fields of study in recent decades. The simplex algorithm is one of the mostly used mathematical techniques for solving LP problems. Data envelopment analysis (DEA) is a non-parametric approach based on linear programming to evaluate relative efficiency of decision making units (DMUs). The number of LP models that has to be solved in DEA is at least the same as the number of DMUs. Toloo et al. (Comput Econ 45(2):323-326, 2015) proposed an initial basic feasible solution for DEA models which practically reduces at least 50 % of the whole computations. The main contribution of this paper is in utlizing this solution to implement LU decomposition technique on the basic DEA models which is more accurate and numerically stable. It is shown that the number of computations in applying the Gaussian elimination method will be fairly reduced due to the special structure of basic DEA models. Potential uses are illustrated with applications to hospital data set.

Czech name

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Czech description

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Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

BB - Applied statistics, operational research

OECD FORD branch

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Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2016

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Computational Economics

ISSN

0927-7099

e-ISSN

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Volume of the periodical

47

Issue of the periodical within the volume

3

Country of publishing house

NL - THE KINGDOM OF THE NETHERLANDS

Number of pages

16

Pages from-to

473-488

UT code for WoS article

000371796600007

EID of the result in the Scopus database

2-s2.0-84960391486