A synergistic approach based on fuzzy hybrid best–worst method and scenario planning to optimize biogas strategies

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-makin...

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Veröffentlicht in:Clean technologies and environmental policy Jg. 27; H. 10; S. 5045 - 5068
Hauptverfasser: Semsarian, Hamed, Babazadeh, Reza, Rezaei, Mohsen, Ozturk, Cemalettin
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2025
Springer Nature B.V
Schlagworte:
Alternative energy sources
Artificial neural networks
Biofuels
Biogas
Biomass
Biorefineries
Circular economy
Collaboration
Cooperation
Cost analysis
Decision making
Earth and Environmental Science
Energy
Energy consumption
Energy industry
Energy resources
Environment
Environmental Economics
Environmental Engineering/Biotechnology
Environmental protection
Fossil fuels
Fuzzy logic
Industrial and Production Engineering
Industrial Chemistry/Chemical Engineering
Knowledge management
Literature reviews
Mathematical models
Matrix methods
Methods
Multiple criteria decision making
Municipal solid waste
Neural networks
Original Paper
Partnerships
Payback periods
Planning
Regression analysis
Reliability
Renewable energy
Renewable energy sources
Renewable fuels
Renewable resources
Research transfer
Scenario planning
Strategic planning
Strategies
Sustainable Development
Uncertainty
Waste management
Iran
Biogas
Artificial neural network
Renewable energy
Uncertainties
Scenario planning
Multi-criteria decision-making
ISSN:1618-954X, 1618-9558
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Zusammenfassung: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
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ISSN:1618-954X
1618-9558
DOI:10.1007/s10098-025-03155-3