A synergistic approach based on fuzzy hybrid best–worst method and scenario planning to optimize biogas strategies - Semsarian, Hamed; Babazadeh, Reza; Rezaei, Mohsen; Ozturk, Cemalettin (Clean technologies and environmental policy, 2025)
Developing effective strategies for harnessing renewable biogas energy is critical. This study introduces a novel hybrid mathematical model integrating scenario-based planning and fuzzy logic, focusing on utilizing biogas as a renewable energy source in Iran. The model aims to enhance decision-making precision amidst uncertainties, aligned with Iran’s Seventh Development Plan, with a planning horizon of 10 years. Through rigorous analysis, three favorable scenarios are identified and evaluated using the proposed fuzzy hybrid best–worst method (FHBWM). Compared to other decision-making approaches, the FHBWM demonstrates improved reliability of weight assignments, flexibility through the importance coefficient ρ , and enhanced consistency management, making it particularly suited for scenario-based problems. Regression analysis and artificial neural network methods are utilized for predicting the oil price and renewable energy production in Iran. Delphi and cross-impact matrix methods are conducted to specify the trend of scenarios. This research highlights the critical role of robust strategies, especially collaborative partnerships, in navigating uncertainties within renewable energy decision-making frameworks. Our study reveals that enhancing cooperation between industries and academic institutions, by streamlining interactions and knowledge exchange, can catalyze advancements in biorefinery technologies. Such policy initiatives can increase efficiency and competitive edge of these technologies and reduce costs, thereby expediting the progression of biofuel development and diminishing dependence on non-renewable fuels. Graphical Abstract