A Multicriteria Decision-Making Method Based on the Strict Ranking Metric Procedure and the Compromise Logic of VIKOR

This paper introduces VIKOR-METRIC, a novel group multi-criteria decision-making (MCDA-G) approach designed to overcome two major limitations of conventional methods: the compensatory effects caused by traditional aggregation operators and the rigorous handling of tied alternatives.Classical aggregation techniques, which merge individual evaluation matrices into a single collective matrix through disjunctive or compromise operators, often lead to information loss and compensatory bias.To address these issues, VIKOR-METRIC integrates the VIKOR method with the Strict Ranking Metric Procedure (SRMP).In the proposed framework, VIKOR is first applied independently to each decision maker's evaluation matrix, producing an individual ranking.These individual rankings are then aggregated using the SRMP, which seeks a consensus ranking by minimizing pairwise disagreements.This process avoids direct data fusion while preserving the diversity of individual preferences.Comparative experiments with existing approaches, notably CHEMATRE, highlight the superior performance of VIKOR-METRIC.The proposed method yields more consistent rankings that better reflect collective preferences and remain free from the biases inherent in traditional aggregation.Consequently, VIKOR-METRIC is particularly suitable for complex decision-making contexts where artificial compensation among criteria is undesirable, such as in public policy evaluation or strategic project management.