Abstract
AbstractThis paper presents a new output‐oriented classification of multiple attribute decision‐making (MADM) techniques, not based on common subjective comparisons, but mostly on quantitative and computer‐aided comparisons and results. Several classifications of MADM techniques exist, all of which are either input‐oriented (based on the type of input data) or process‐oriented (depending on the process of calculating the final results using the input data). The classification provided in this paper is based on measuring the performance of 17 MADM techniques (SAW, ELECTRE I, TOPSIS, ORESTE, PROMETHEE I, EVAMIX, MAUT, REGIME, MAPPAC, TACTIC, VIKOR, ARGUS, COPRAS, SMART, PACMAN, MOORA, and ARAS) in seven performance variables (simplicity in learning and deploying, speed, complexity of calculations, the number of inputs, the quality of the underlying logic, the quality of rankings, and the rate of growth in large problems) and clustering them using fuzzy c‐means clustering method. Results indicate that the considered techniques can be best classified into two clusters.
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