Analysing environmental investments in industrial water reuse with artificial decision support systems including hybrid multi-facet fuzzy optimization

• Proposes an AI-supported multi-facet fuzzy model for industrial water reuse investments. • Introduces dynamic fuzzy sets to handle multidimensional uncertainty. • Integrates LLSW and PCRO for robust weighting and ranking. • Identifies circularity as the most critical investment criterion. • Highlights modular units and reuse networks as optimal strategies. Water reuse in industry has become a strategic necessity for environmental investments. However, a fundamental problem in this area is the uncertainty faced by industrial enterprises in their decision-making processes regarding which criteria should be prioritized, and which strategies should be implemented due to limited budgets. Studies systematically evaluating the criteria and strategic alternatives that influence the performance of environmental investments in industrial water reuse are quite limited. This deficiency hinders decision-makers' scientifically based prioritization when planning environmental investments and hinders effective resource management. The primary objective of this study is to provide decision-makers with a systematic evaluation model by identifying the most important criteria and the most appropriate strategy alternatives for environmental investments in industrial water reuse. To this end, a new artificial intelligence-supported fuzzy decision-making model is being developed to enable reliable and holistic analysis in an environment of uncertainty. The model is based on five criteria identified through a literature review and various strategy alternatives and enhances analytical power by amplifying expert opinions through artificial decision support systems. Criteria importance weights are calculated using the logarithmic least-squares weighting method (LLSW), and the ranking of strategy alternatives is calculated using the principal component ranking optimization technique. Additionally, the dynamic multi-facet fuzzy set structure developed in this study provides a novel contribution to the literature in representing multidimensional uncertainties. The advantages of the proposed model include increased reliability through AI-based amplification of expert opinions, increased evaluation flexibility with the new fuzzy set structure, and preservation of proportional consistency through the LLSW method. The findings indicate that circularity is the most important criterion for environmental investments in industrial water reuse. Numerical validity and algorithmic accuracy are verified using internal consistency residuals (LLSW fit), robustness statistics (Spearman’s ρ and Kendall’s W), and benchmark agreement with Extended TOPSIS.