Hello!
Multiple Criteria Decision-Making (MCDM) methods are applied in many fields of science, as a result, many scientific publications related to the application of these methods have been prepared.
Some of the most popular MCDM methods or MADM (Multiple Attribute Decision-Making) are TOPSIS, SAW, AHP, etc. In describing these methods, some authors use the term "criteria", and others use the term "attribute". I would like to know your opinion on which term should be used.
Some references:
Yoon, K. P., & Hwang, C. L. (1995). Multiple attribute decision making: an introduction. Sage publications.
Triantaphyllou, E. (2000). Introduction to Multi-Criteria Decision Making. In: Multi-criteria Decision Making Methods: A Comparative Study. Applied Optimization, vol 44. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-3157-6_1
Thank you!
Perhaps both terms are used interchangeably to avoid triggering similarity software. Still, I tend to favor criteria and not attributes as it is perceived to be associated with decision-making.
Dear Ruta
In my opinion, the correct name is 'criteria'. Attibutes define the elements that make a criteria, and performance values are the numebrs with whch each alternative contributes to each criterion.
Since an atribute defines a criterion, they tell us about the characteristics for each one, like type of performance factors , i.e., negatives, positives, integer, decimal or their dispersion. The action maximize or minimze a criterion, defines its puropse, normally benefit, costs or equal.
In addition, each criterion is an objective to whcih each alternative must comply, and in this sense, they need a goal, for instance, in criterion ' CO2 contamination', which of course must be minimzed, we need to put a nuneric value that indicates the maximum amount of contamination allowed
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