FARKLI NORMALİZASYON TEKNİKLERİNİN ÇOK KRİTERLİ KARAR VERME YÖNTEMLERİNE ETKİSİ: WASPAS ÖRNEĞİ

Multi-Criteria Decision Making (MCDM) methods are used to select the most suitable alternatives in line with the determined criteria. Since the criteria have different measurement units, normalization methods are used to make the measurement units of the criteria dimensionless. However, there is no consensus on which normalization technique should be used in which MCDM method. The aim of this study is to investigate how 7 different normalization techniques affect the results of the WASPAS method, which is one of the MCDM methods. In practice, the performance of 7 vacuum cleaners belonging to different companies, which are small household appliances and whose names are kept confidential, was evaluated under 6 criteria. Shapiro Wilk test was used to analyze the conformity of WASPAS results to normal distribution. Pearson correlation test was applied to normally distributed results and the relationship between normalization techniques was examined. When the results obtained were examined, it was seen that Linear Normalization (Sum) and Vector Normalization techniques could be used as an alternative to the normalization technique used in the original for the WASPAS method. It was concluded that Linear Normalization (Max-Min) technique gave the worst results compared to other normalization techniques and was not suitable for the WASPAS method.