An Enhanced QAOM-Based MAGDM Framework: ‎Integrating Entropy Weighting and Expert Judgment Aggregation

Addressing complex decision-making scenarios‎, ‎particularly those involving multiple criteria and expert perspectives‎, ‎often requires robust frameworks capable of managing uncertainty and qualitative assessments‎. ‎The Qualitative Absolute Order-of-Magnitude (QAOM) model offers a flexible approach for expressing subjective evaluations through linguistic terms with adjustable levels of detail‎. ‎However‎, ‎practical challenges remain in applying QAOM‎, ‎including the absence of an inherent system for deriving attribute weights‎, ‎limitations in coherently synthesizing the judgments from multiple experts‎, ‎and the lack of systematic normalization procedures for negatively oriented attributes‎. ‎To address these issues‎, ‎this paper proposes an advanced multi-attribute group decision-making (MAGDM) framework fully embedded within the QAOM paradigm‎. ‎The proposed solution introduces a mathematically consistent metric for comparing linguistic assessments‎, ‎an entropy-based attribute weighting approach rooted in qualitative information‎, ‎and an aggregation process that reflects expert diversity‎. ‎Furthermore‎, ‎a specialized normalization protocol is developed to handle negative attributes across heterogeneous scales‎. ‎The feasibility and advantages of the method are validated through comprehensive examples and comparative analyses‎, ‎highlighting improvements over traditional techniques in terms of objectivity‎, ‎flexibility‎, ‎and analytical depth‎. ‎Overall‎, ‎these developments markedly enhance the capabilities of QAOM-based MAGDM‎, ‎equipping decision-makers with more nuanced and reliable tools for tackling complex problems characterized by imprecision and divergent expert opinions‎.

کلیدواژه ها:

Qualitative reasoning‎ ، ‎Multi-attribute decision making ، ‎Ranking ، ‎Qualitative absolute order-of-magnitude