Selection of best location for household waste recycling plants using novel information measures and algorithm in fermatean fuzzy environment

Abstract

The selection of appropriate locations for household waste recycling plants is a critical issue due to its impact on environmental sustainability and waste management efficiency. By finding the best spot, we can make recycling more efficient, reduce pollution, and improve sustainability. This study presents innovative methods within the Fermatean fuzzy sets (FFSs) specifically, we introduce a novel distance measure, a logarithmic score function, an entropy measure and using this measures we introduced an integrated method combining Entropy Measure (EM), Step-wise Weight Assessment Ratio Analysis (SWARA), and Weighted Aggregated Sum Product Assessment (WASPAS) methods for this purpose. Fermatean fuzzy sets provide a broader range of membership, nonmembership, and hesitation values, offering greater flexibility and expressiveness in evaluating alternatives. Our proposed measures and the algorithm are compared with existing measures and the methods in the FFSs environment, demonstrating their reliability and superiority by addressing the limitations of existing measures and methodologies. This combined framework leverages both subjective (by SWARA) and objective (by Entropy Measure) weighting to comprehensively evaluate alternatives against multiple criteria and experts which is free from biases towards one particular weight model. The innovative distance measure and score function significantly improve decision-making reliability with the help of our proposed algorithm, especially under conditions of uncertainty. Experimental results and a real-life case study confirm that our approach not only provides finer differentiation than existing fuzzy techniques but also enhances the robustness and accuracy of MCDM outcomes. This advancement is particularly valuable in the context of selecting optimal locations for household waste recycling plants, contributing to more effective and sustainable waste management solutions.