A Complex Fuzzy MAGDM Framework for Sustainable Gold Mining using Hamacher Aggregation Operators

Abstract

Cleaner Production (CP) is widely recognized as a key strategy for balancing environmental protection with economic development in industrial sectors, including gold mining. In this study, we propose a novel multi-attribute group decision-making (MAGDM) model based on Complex 𝑝,𝑞-Rung Orthopair Fuzzy Sets (Cp,զ-ℛՕFՏs) and Hamacher Aggregation Operators (HAOs) to evaluate sustainability-driven decisions in gold mining operations. The model captures the complex and uncertain nature of expert assessments using complex-valued membership structures and flexible aggregation processes. To demonstrate the model’s practical utility, a real-world-inspired case study involving the evaluation of five cleaner production alternatives in a gold mining scenario is conducted. These alternatives are assessed based on environmental, economic, and technical criteria. The proposed framework effectively aggregates expert opinions under uncertainty, and a detailed comparative and sensitivity analysis validates the robustness and precision of the method. Results show that the model supports informed and sustainable decision-making in mining practices, offering a promising tool for industries seeking to implement CP under uncertain and complex conditions.