Akademik Veri Yönetim Sistemi
3. ULUSLARARASI İSTATİSTİK MATEMATİK VE ANALİTİK YÖNTEMLER KONGRESİ, İstanbul, Türkiye, 12 - 13 Mart 2020, ss.53
Using appropriate data in decision-making
problems is important to achieve better results. Since having the
unpredictability information of the data to be utilized will increase the
validity of the solution, the fuzzy set theory has had a serious effect on
decision making methods. Therefore, we handle TOPSIS (Technique for Order of
Preference by Similarity to Ideal Solution) which is one of MCDM (Multiple
Criteria Decision Making) methods by using fuzzy sets. Although working with
type-1 fuzzy sets is more difficult than crisp numbers, it can be counted
easily enough. However, they are not good enough to process unknown materials.
This deficiency led to the emergence of a more competent concept in the
literature. Type-2 fuzzy sets that are a special form of fuzzy sets can reflect
uncertainty much better than type-1 fuzzy sets. However, the processing density
of these sets has made their use quite difficult. In order to alleviate the
operations, interval type-2 fuzzy sets have been developed, and these sets have
been used widely in MCDM methods. Hence, interval type-2 fuzzy set theory is
addressed to overcome uncertainty more realistically in our study. We adapt the
previous work done on risk assessment with type-1 fuzzy sets to interval type-2
fuzzy sets by using TOPSIS. The aim of this study is to observe results by
considering these works.