FMIAT: Frequency Matrix Inclusion Analysis Technique for MCDM

Abstract

The wider applicability of inclusion measures as well as the diversity of data existing in real life situations has motivated most of the researchers to introduce a two degree inclusion indicator within the intuitionistic fuzzy framework. Although these measures are capable of portraying the level of inclusion as well as a non inclusion relation existing between objects under consideration yet, they lose their practical application due to their computational complexity in many decision making situations. In our view, a single fuzzy degree intuitionistic inclusion measure will serve the purpose more effectively rather than a two degree inclusion measure for intuitionistic fuzzy sets. Therefore, in this research work we present a new yet effective technique to solve the Multi-Criteria Decision Making problems in intuitionstic fuzzy environment based on single degree inclusion measures called The Frequency Matrix Inclusion Analysis Technique (FMIAT). This new technique is much simpler than any of the previously introduced techniques for MCDM in literature which makes it economically viable. The technique utilizes the Parametric family of Fuzzy Inclusion Measures for IFS's introduced in [Qayyum M. (2017) New Measures of intuitionistic inclusion and similarity with applications, PhD Thesis, COMSATS University Islamabad, Lahore Campus] as fundamental tool of analysis whose members in their own construction are based on variety of t-norms and t-conorms. This possible variation of t-norms and t-conorms gives our technique a clear advantage over other techniques as it becomes more flexible and can deal with all the three different states of mind (being Pessimist, Optimist and Neutral) of a decision maker by use of different operators in the respective inclusion indicators. Finally, an application of this technique is made in the field of Organizational Management.