A new approach for solving rough interval mcdm problems based on bwm and waspas methods

Abstract

The process of ranking alternatives in Multi-Criteria Decision Making (MCDM) problems with rough intervals is a situation really tough to handle. Despite, there are dozens of proposals to handle MCDM problems under different types of uncertainty but still there is limited number of articles to explore Rough MCDM specially, the rough interval ones with no weights for criteria. Mainly, this research is to propose a new approach combining two novel methods to treat such MCDM problems. First, Rough Interval Best-Worst Method (RIBWM), where RIBWM is applied for assigning weights to criteria based on the criteria preference given by the Decision Makers (DMs). This is done in a new manner to handle rough interval preference given. Second, a new Rough Interval Weighted Aggregated Sum-Product Assessment method (RIWASPAS) is presented to rank the alternatives. A merit of this new approach that it sustains rough interval representation of the problem till the end as well as it deals with it efficiently. Finally, an illustrative example is provided for validation.