Shadowed AHP for multi-criteria supplier selection
Mohamed Abdel Hameed El-Hawy

TL;DR
This paper introduces a novel Shadowed AHP method that effectively handles multi-granular uncertain preference data in multi-criteria supplier selection, enhancing decision-making accuracy.
Contribution
The paper proposes a new Shadowed AHP approach using shadowed fuzzy numbers to unify and process multi-granular uncertain preferences in decision-making.
Findings
Successfully applied to supplier selection problem
Improves handling of multi-granular uncertain data
Provides a new ranking method for preferences
Abstract
Numerous techniques of multi-criteria decision-making (MCDM) have been proposed in a variety of business domains. One of the well-known methods is the Analytical Hierarchical Process (AHP). Various uncertain numbers are commonly used to represent preference values in AHP problems. In the case of multi-granularity linguistic information, several methods have been proposed to address this type of AHP problem. This paper introduces a novel method to solve this problem using shadowed fuzzy numbers (SFNs). These numbers are characterized by approximating different types of fuzzy numbers and preserving their uncertainty properties. The new Shadowed AHP method is proposed to handle preference values which are represented by multi-types of uncertain numbers. The new approach converts multi-granular preference values into unified model of shadowed fuzzy numbers and utilizes their properties. A…
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