NOVEL FUZZY MODIFIED TOPSIS METHOD FOR MULTI CRITERIA DECISION MAKING IN AGRICULTURE

Abstract

Making decisions in agriculture is inherently complex due to uncertainty, imprecision, and the involvement of multiple conflicting criteria. This paper suggests a Novel Fuzzy Modified TOPSIS approach for resolving multi-criteria decision-making (MCDM) issues in the agricultural field in order to overcome these difficulties. The proposed approach integrates fuzzy logic with a modified distance-based ranking mechanism to better capture the vagueness in expert judgments and improve discrimination among alternatives. Unlike the conventional Fuzzy TOPSIS, the modified formulation enhances normalization, weighting, and closeness co efficient computation for more robust and reliable rankings. The applicability of the proposed method is demonstrated through agricultural decision scenarios such as crop selection and irrigation strategy evaluation. Results indicate that the novel Fuzzy Modified TOPSIS method provides superior stability, sensitivity, and practical relevance compared to traditional methods, making it an effective decision-support tool for sustainable agricultural planning. This study compares the Fuzzy TOPSIS and Novel Fuzzy Modified TOPSIS methods using an example, and the results demonstrate that FM-TOPSIS is a useful tool for agricultural decision-making.