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A Comment on Theory of Integer-Valued Data Envelopment Analysis

Dariush Khezrimotlagh, Shaharuddin Salleh, Zahra Mohsenpour

Open publisher page 9 citations

Abstract

The mixed-integer linear programming data envelopment analysis models were proposed due to this reason that the conventional DEA models may suggest some non-integer values for the inputs and/or outputs of decision making units (DMUs) which those data can only be specified with integer values such as the number of employees and books. There are a few researches on integer-valued DEA and this paper focuses on the three previous ones. The paper characterizes some shortcomings on those researches with some mathematic logics.

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What this paper is about

The mixed-integer linear programming data envelopment analysis models were proposed due to this reason that the conventional DEA models may suggest some non-integer values for the inputs and/or outputs of decision making units (DMUs) which those data can only be specified with integer values such as the number of employees and books. There are a few researches on integer-valued DEA and this paper focuses on the three previous ones. The paper characterizes some shortcomings on those researches with some mathematic logics.

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OpenAlex reports 9 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

The mixed-integer linear programming data envelopment analysis models were proposed due to this reason that the conventional DEA models may suggest some non-integer values for the inputs and/or outputs of decision making units (DMUs) which those data can only be specified with integer values such as the number of employees and books. There are a few researches on integer-valued DEA and this paper focuses on the three previous ones. The paper characterizes some shortcomings on those researches with some mathematic logics.

Key concepts: Data envelopment analysis, Integer (computer science), Integer programming, Linear programming, Mathematical optimization, Mathematics, Computer science, Operations research

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