Multi-Criteria Decision Making (MCDM) methods refer to mathematical techniques used in a wide range of fields such as production, education, health, economy, military. There are many MCDM alternatives to solve a decision problem and it is often left to the researcher which method to use. Researchers most prefer to heuristically choose one of these MCDM alternatives. Since the inception of the development of MCDM methods, the choice of the right MCDM model has depended on an analysis set for which the available data is sufficient, as any decision problem is the way in which it elicits strong decision making meaning. Thus, MCDM has become a sort of data-based Meta selection problem. There are several selection approaches to deal with this Meta selection problem. However, some of these meta-selection approaches take very obvious aspects (ignoring some important factors) for meta-selection, while others choose very complex paths (takes too much time). It suggests that in order to design a robust and useful Meta selection approach, it is necessary to treat the model selection problem as the MCDM problem itself. Based on this idea, AHP, ANP, TOPSIS, ELECTRE, the selection approach on alternatives that can be used to solve the specific decision problem is exhibited in this study. The evaluation of alternatives according to some criteria specific to the problem area and the expectations of the decision maker will also be covered within the scope of the study. As it is known, all MCDM models have some structural features, which we call ontological features, according to their existence purposes. In this context, primarily, these structural features have been redefined within the scope of the study.

The study also includes a template introduction that will allow the decision maker to compare these features according to their own requirements. The example of the application template of the model is handled through the primary machine selection problem for a medium-sized fishing vessel. The sample template also includes comparing TOPSIS, ELECTRE, PROMETHEE and AHP with each other as alternative methods to solve this decision making problem.

First, we list the ontological features of these alternative methods, and then we determine some selection criteria such as convenience, flexibility, validity, opinion of the decision maker, characteristics of the criteria, and qualitative-quantitative criteria. Considering the uncertainty of these criteria, we prefer Fuzzy AHP as the way to choose the most appropriate decision making method specific to our decision problem. In this context, we present a new approach to method selection and provide framework modeling for a rationalized support for the chosen method.