Hybrid MCDM Model of ARAS -TOPSIS - GRA for Materials Selection Problem

Abstract

Since traditional Multi-Criteria Decision Making (MCDM) approaches have become defunct, academics have shifted their attention to developing hybrid MCDM models, which use a combination of two or more MCDM methods to solve decision-making issues. Using Additive Ratio Assessment (ARAS), the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), and Gray Relational Analysis (GRA), the authors of this work aimed to develop unique hybrid MCDM systems. To show how well this hybrid model works, it is applied to a real-world material selection scenario including seven possible materials and seven criteria. Results from this hybrid model are compared to those from other standalone MCDM tools as well as previously published findings based on the same illustrative situation. 3rd Material is the best option, while the 2nd material is the worst option, among these seven choices which are consistent enough to imply such a conclusion. Using many MCDM strategies is recommended since no one strategy can ensure making the best decision. Because of this, the Copeland approach is used to combine the rankings from the 11 methodologies and get a consensus result. The results from the Copeland technique show that the final consensus rank of materials may be different from the rank of the hybrid model and other standalone MCDM tools. As a result, it is crucial to use a multi-pronged approach. Furthermore, the Spearman Correlation Coefficient (SCC) shows that the suggested rankings produced from the different approaches have a significant ranking association with one another.

Keywords

• hybrid mcdm
• aras
• topsis
• gra
• material selection