The role of non-Archimedean epsilon in finding the most efficient unit: with an application of professional tennis players

DOI10.1016/j.apm.2014.04.010zbMath1428.90088OpenAlexW2015328411WikidataQ57840768 ScholiaQ57840768MaRDI QIDQ1634131

Mehdi Toloo

Publication date: 17 December 2018

Published in: Applied Mathematical Modelling (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.apm.2014.04.010

zbMATH Keywords

data envelopment analysisintegrated modelmost efficient unitnon-Archimedean epsilon

Mathematics Subject Classification ID

Applications of mathematical programming (90C90) Management decision making, including multiple objectives (90B50)

Related Items (8)

Refined bounds for the non-Archimedean \(\epsilon\) in DEA ⋮ Selecting slacks-based data envelopment analysis models ⋮ A minimax approach for selecting the overall and stage-level most efficient unit in two stage production processes ⋮ Selecting most efficient information system projects in presence of user subjective opinions: a DEA approach ⋮ New data envelopment analysis models for classifying flexible measures: the role of non-Archimedean epsilon ⋮ A method for evaluating the performance of decision making units with imprecise data using common set of weights ⋮ A common-weight DEA model for multi-criteria ABC inventory classification with quantitative and qualitative criteria ⋮ An integrated data envelopment analysis and mixed integer non-linear programming model for linearizing the common set of weights

Cites Work

• Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis
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• A new integrated DEA model for finding most BCC-efficient DMU
• A multiple criteria approach to data envelopment analysis
• An effective non-Archimedean anti-degeneracy/cycling linear programming method especially for data envelopment analysis and like models
• A polynomial-time algorithm for finding \(\varepsilon\) in DEA models
• Review of ranking methods in the data envelopment analysis context
• On finding the most BCC-efficient DMU: a new integrated MIP-DEA model
• An improved MCDM DEA model for technology selection
• Computational Accuracy and Infinitesimals In Data Envelopment Analysis
• Practical common weight multi-criteria decision-making approach with an improved discriminating power for technology selection
• Nonlinear Programming
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