Akademik Veri Yönetim Sistemi
JOURNAL OF POLYTECHNIC-POLITEKNIK DERGISI, cilt.25, sa.2, ss.799-811, 2022 (ESCI)
Entropy, developed to measure information uncertainty, is taken place in the literature as an important concept after adapting to the fuzzy set theory. Fuzzy entropy gives a measure of the uncertainty of the situation, which is considered the average amount of information lost when passing from a classical pattern to the fuzzy pattern. One of the areas where entropy is used is multi-criteria decision making (MCDM) problems. In some of the studies on MCDM problems, entropy is used to calculate weights of criteria or experts, or to rank alternatives. In this study, the compatibility of entropy measures developed for the interval-valued intuitionistic fuzzy (IVIF) environment with MCDM problems is investigated. As a result of the exemplary calculations and discussions, it is seen that that the entropy functions developed for ADSB clusters does not work effectively in MCDM problems due to its theoretical properties.