Voting-KEMIRA method for determining criteria priority and weights in solving multi-attribute decision making problems

Abstract

The KEmeny Median Indicator Ranks Accordance (KEMIRA) method [1] is one of the newest Multi-Attribute Decision Making (MADM) methods that is used for problems in which criteria are inherently divided into two or more categories. Increasing computational complexity in the face of large-scale problems as well as the inflexibility of the method in increasing the categories of criteria are among the disadvantages of this method. Preferential voting is a decision-making method based on a linear programming model with weight restrictions [2], which in combination with KEMIRA can significantly eliminate its shortcomings. This talk presents the new Voting-KEMIRA method to achieve this purpose, which is more flexible and has less computational complexity. The new hybrid method is implemented on a real–world problem and compared to the previous method.