A novel pairwise comparison method with linear programming for multi-attribute decision-making

Abstract

This study introduces a novel approach to effectively and efficiently solve Multi-Attribute Decision Making (MADM) problems with a considerable number of attributes. We demonstrate the need to categorize the attributes and facilitate a more systematic expert comparison. Our proposed method utilizes pairwise comparisons to assess attributes without requiring additional computations to evaluate the level of consistency. The proposed method offers greater flexibility and precision with reduced computational complexity. We present a comparative analysis with a widely used numerical example in the MADM literature to demonstrate the effectiveness and efficacy of the method proposed in this study.