Improved Kemeny Median Indicator Ranks Accordance Method

Mehdi Soltanifar ()
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Mehdi Soltanifar: Department of Mathematics, Semnan Branch, Islamic Azad University Semnan, Iran

Asia-Pacific Journal of Operational Research (APJOR), 2023, vol. 40, issue 03, 1-20

Abstract: Multi-attribute decision-making (MADM) methods are widely used by decision makers as decision support tools. Most MADM methods have shortcomings in the solution process that combined with other decision making methods can eliminate these shortcomings or improve the performance of the method. One of the methods that can be used to improve MADM methods is preferential voting, which is actually a linear programming (LP) model with weight restrictions. The Kemeny Median Indicator Ranks Accordance (KEMIRA) is one of the most modern MADM methods; in this paper, we provide an improved version in this relative, by utilizing the concept of preferential voting. The new model, in being implemented on a real-world problem, will be compared to the previous method and ultimately some of its advantages will be rendered.

Keywords: Decision support system; multi-attribute decision-making (MADM); Kemeny Median Indicator Ranks Accordance (KEMIRA); weight restrictions; preferential voting (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1142/S0217595922500245

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