Multi-criteria decision-making model based on picture hesitant fuzzy soft set approach: An application of sustainable solar energy management

This study addresses the optimization of energy management within corporations to reduce expenditures and maximize profits. Focusing on proactive, coordinated, and systematic energy usage, the research emphasizes the importance of informed decisions through building management, energy audits, and equipment retrofits. The proposed concept of Picture Hesitant Fuzzy Soft Set (PHFSS) with Archimedean aggregation operators, featuring Einstein generators, is introduced. Various aggregation techniques, including PHFS weighted, weighted ordered, weighted geometric, ordered weighted geometric, and hybrid operators, are thoroughly examined. PHFSS is utilized to represent ambiguous information in decision-making processes. The study introduces a novel multi-criteria decision-making (MCDM) method to address the challenge of selecting optimal energy management sources, demonstrating its effectiveness through a large-scale numerical example. This approach surpasses the distance from average solution (EDAS) method in terms of effectiveness and reliability. The research contributes valuable insights into optimizing energy management, reducing costs, and mitigating environmental impact.