Multicriteria Decision Making: Scale, Polarity, Symmetry, Interpretability

In this study, we discuss the problem of interpretability of scale versus polarity in multicriteria decision-making problem. Decision making requires aggregation of premises of different characters and types. The influence of premises on a decision to be made may have a different characteristics as well. Some premises may have a positive character, i.e. they vote/agitate towards making a decision, others may fight against a decision. On the other hand, premises can be tempered by priorities, which may affect their character. Therefore, there is a need to discuss different configurations of premises and their priorities. This is the first aspect of our discussion on multicriteria decision making. The second one under discussion is the interpretability of all aspects mentioned so far. In this case, we discuss the representation problems of both premises and priorities. They are usually exhibited as numbers taken from some scale as, for instance, the unipolar unit interval [0,1] or the bipolar unit interval [−1,1]. On the other hand, there is a question raised about a character of premises/priorities, that is, whether they vote pro or contra a decision to be taken and what relations between scales and polarities are.

[1]  Krassimir T. Atanassov,et al.  Intuitionistic fuzzy sets , 1986 .

[2]  Ronald R. Yager,et al.  Information Processing and Management of Uncertainty in Knowledge-Based Systems , 2014, Communications in Computer and Information Science.

[3]  Witold Pedrycz,et al.  Processing uncertain information in the linear space of fuzzy sets , 1991 .

[4]  Bruce G. Buchanan,et al.  The MYCIN Experiments of the Stanford Heuristic Programming Project , 1985 .

[5]  K. Menger Statistical Metrics. , 1942, Proceedings of the National Academy of Sciences of the United States of America.

[6]  W. Silvert Symmetric Summation: A Class of Operations on Fuzzy Sets , 1979 .

[7]  Qing He,et al.  Beyond Polarity: Interpretable Financial Sentiment Analysis with Hierarchical Query-driven Attention , 2018, IJCAI.

[8]  A. Tversky,et al.  Prospect theory: an analysis of decision under risk — Source link , 2007 .

[9]  Witold Pedrycz,et al.  Multicriteria decision making inspired by human cognitive processes , 2016, Appl. Math. Comput..

[10]  Maciej Wygralak,et al.  A Bipolar View on Medical Diagnosis in OvaExpert System , 2015, FQAS.

[11]  R. Yager Families of OWA operators , 1993 .

[12]  Uzay Kaymak,et al.  Information Processing and Management of Uncertainty in Knowledge-Based Systems , 2016, Communications in Computer and Information Science.

[13]  Bernard De Baets,et al.  The functional equations of Frank and Alsina for uninorms and nullnorms , 2001, Fuzzy Sets Syst..

[14]  Charles Higgins Kepner,et al.  The Rational Manager: A Systematic Approach to Problem Solving and Decision-Making , 1965 .

[15]  Robert LIN,et al.  NOTE ON FUZZY SETS , 2014 .

[16]  Witold Pedrycz,et al.  Symmetrization of Fuzzy Operators: Notes on Data Aggregation , 2002, FSKD.

[17]  B. Bouchon-Meunier,et al.  Aggregating truth and falsity values , 2000, Proceedings of the Third International Conference on Information Fusion.

[18]  T. Saaty Decision making — the Analytic Hierarchy and Network Processes (AHP/ANP) , 2004 .

[19]  Berthold Schweizer,et al.  Probabilistic Metric Spaces , 2011 .

[20]  Bernadette Bouchon-Meunier,et al.  Building an Aggregation Operator with a Balance , 2000 .

[21]  Christian Eitzinger,et al.  Triangular Norms , 2001, Künstliche Intell..

[22]  Ronald R. Yager,et al.  Uninorm aggregation operators , 1996, Fuzzy Sets Syst..

[23]  James C. Bezdek,et al.  Pool2: a generic system for cognitive map development and decision analysis , 1989, IEEE Trans. Syst. Man Cybern..

[24]  Didier Dubois,et al.  Gradualness, uncertainty and bipolarity: Making sense of fuzzy sets , 2012, Fuzzy Sets Syst..

[25]  Ronald R. Yager,et al.  Full reinforcement operators in aggregation techniques , 1998, IEEE Trans. Syst. Man Cybern. Part B.

[26]  W.-L. Gau,et al.  Vague sets , 1993, IEEE Trans. Syst. Man Cybern..