Risk-based decision-making

In complex decision-making processes using multi-criteria decision-making methods, experts' beliefs and judgments, as well as their knowledge, are influential in the comparisons between criteria and alternatives, which may lead to overlapping importance rankings of criteria. In this study, to increase the degree of representativeness of uncertainties in overlapping criteria evaluations, a correction term is integrated into the fuzzy entropy method, so that the risk cost levels of the main criteria of equal importance differ according to the number of sub-criteria. The integrated correction term into the fuzzy entropy calculation is proposed as a relative importance weight multiplier in the two-dimensional fuzzy AHP process steps. Although the \(\alpha\)-alpha truncation method is proposed for the Fuzzy AHP method, the decision matrix is converted into crisp values in the process stages and directly reduced to the Classical AHP method. Within this article, using the judgment matrix with interval values is proposed instead of exact judgment values as to not distort the fuzzy structure of the result values. In the article, the two-dimensional fuzzy Entropy weights obtained by using the alpha-cutting method can be used as a relative importance weight multiplier in the fuzzy AHP process proposed in two dimensions to obtain clear importance rankings of the criteria. Thanks to the method approach proposed, OCTAVE Allegro logic is combined to create a relative risk matrix according to the risk environment conditions for the criteria alongside the ranking level.