Abstract
The Characteristic Objects METhod (COMET) is a relatively new, rank reversal free, a multi-criteria decision-support technique based on fuzzy set theory. The advantages of this method include high accuracy and flexibility of the obtained results. A decision-maker defines each criterion’s characteristic values, decomposes the complex problem into a structured approach, or uses a monolithic approach to solve a problem. The current form of the algorithm uses product and sum as functions to model intersection and union. However, it is also possible to choose another T-norm and S-norm operators instead of the initially proposed operators. This study examines whether T-norm and S-norm operators’ selection influences the final ranking obtained using the COMET method. For this purpose, we present an experiment based on similarity coefficients of rankings, which allows us to study the differences in rankings when using different pairs of operators. The main contribution is that using another set of the fuzzy operator can significantly influence the final similarity results.
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The work was supported by the National Science Centre, Decision number UMO-2018/29/B/HS4/02725.
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Shekhovtsov, A., Kizielewicz, B., Sałabun, W. (2022). Intelligent Decision Making Using Fuzzy Logic: Comparative Analysis of Using Different Intersection and Union Operators. In: Kahraman, C., Cebi, S., Cevik Onar, S., Oztaysi, B., Tolga, A.C., Sari, I.U. (eds) Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation. INFUS 2021. Lecture Notes in Networks and Systems, vol 307. Springer, Cham. https://doi.org/10.1007/978-3-030-85626-7_24
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