Fuzzy multiple attribute decision making – university as an example
DOI:
https://doi.org/10.37886/Keywords:
multiple attribute decision making, alternatives, criteria, fuzzy set, ranking, universityAbstract
Research Question (RQ): The establishment of the university (in a certain place, it can also be University of Novo mesto) is time-consuming and extremely important process. A lot of criteria that influence on the decision as to what form of organization would be rational and advantageous should be taken into account. The question on which it will be answered is: is it possible to use quantitative methods to identify meaningful organizational structure of the University and how do we do that?
Purpose: The aim and objective of the research is to answer the above question and thereby give decision makers the possibility to use additional neutral informations.
Method: In the research the method of multiple attribute decision making is used. With the combination of AHP method and algorithm VIKOR a solution to the problem is given, when the input data are crisp numbers. However, since the input data are often, especially in the case of the University mainly descriptive and ambiguous terms, we have to use the principles (theorems) of fuzzy logic. Synthesis of the both methods is the fuzzy multiple attribute decision making method and used in this research.
Results: The results of the research show that scientific instruments that are used are meaningful and unambiguously answer the question. Of course, as with any quantitative method, it is necessary to take into account the robustness of the input data.
Organization: The research results can have a direct impact on the decisions of the organization of a possible new university.
Society: Impact of the research on society, social responsibility and the environment is direct, since with used algorithm these components are taken into account.
Originality: The study is original in (at least) two aspects: a) it defines the introduction of fuzzy sets in one of the methods of operation research and thus enables great flexibility in the use of partially imprecision and only in words defined criteria / data and b) it applies an algorithm to the establishment of the University, which is new in the literature.
Limitations/Future Research: Limitations and also (paradoxically) the benefits of the research are in the interpretation and application of the input data. Continued research should go in the direction of use sensitive analysis of the results and the gradual introduction of an integrated fuzzy approach, in the final phase also in the upgrade of the algorithm with neurofuzzy learning.
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