Extension of the SPOTIS method for the rank reversal free decision-making under fuzzy environment

The growing popularity of the usability of Multi-Criteria Decision Analysis (MCDA) methods has resulted in many studies verifying their applicability and quality of performance. Due to the possibility of different data representation in multi-criteria problems, the issues addressed may be in the space of crisp values or an uncertain environment. In addition, due to the quality of the guaranteed results, methods that provide resistance to the ranking reversal phenomenon are desirable. This paper proposes an extension of the Stable Preference Ordering Towards Ideal Solution (SPOTIS) method, free of the rank reversal phenomenon in multi-criteria problems under a fuzzy environment. The proof of concept was presented based on two numerical examples, presenting the method's performance and usefulness in decision-making. Obtained results showed that the proposed approach could be effectively used when handling the uncertain conditions of multi-criteria problems.