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A platform for research: civil engineering, architecture and urbanism
A Grey-Fuzzy Programming Approach towards Socio-Economic Optimization of Second-Generation Biodiesel Supply Chains
This study aims to develop a multi-objective second-generation-based socially responsible supply chain (SGB-SRSC) network design model that considers all dimensions of sustainability: economy, environment, and social. The dynamic nature of the biodiesel supply chain (SC) impairs the SGB-SRSC model decisions; thus, a grey-fuzzy solution approach is developed. Biodiesel is a promising renewable energy resource produced from a variety of easily accessible domestic wastes. For a swift transition towards commercially feasible biodiesel production, integrated optimization of the biodiesel SC system is critical. Using the latest social impact assessment tools, this study provides a decision-support system for developing a biodiesel SC network. A comprehensive computational analysis is performed on a case study to validate the proposed model. The results show that significant investment is required to achieve social well-being goals and secure decisions against uncertainty associated with SGB-SRSC model parameters. Further, it is observed that the expenses of biodiesel production and biodiesel plant installation accounted for a large portion of the overall SC cost. As a result, finding more cost-effective biodiesel production methods is critical to the industry’s economic viability. Regulators and policymakers involved in biodiesel production projects may find the framework useful in obtaining a compromise solution for socio-economic goals based on their preferences.
A Grey-Fuzzy Programming Approach towards Socio-Economic Optimization of Second-Generation Biodiesel Supply Chains
This study aims to develop a multi-objective second-generation-based socially responsible supply chain (SGB-SRSC) network design model that considers all dimensions of sustainability: economy, environment, and social. The dynamic nature of the biodiesel supply chain (SC) impairs the SGB-SRSC model decisions; thus, a grey-fuzzy solution approach is developed. Biodiesel is a promising renewable energy resource produced from a variety of easily accessible domestic wastes. For a swift transition towards commercially feasible biodiesel production, integrated optimization of the biodiesel SC system is critical. Using the latest social impact assessment tools, this study provides a decision-support system for developing a biodiesel SC network. A comprehensive computational analysis is performed on a case study to validate the proposed model. The results show that significant investment is required to achieve social well-being goals and secure decisions against uncertainty associated with SGB-SRSC model parameters. Further, it is observed that the expenses of biodiesel production and biodiesel plant installation accounted for a large portion of the overall SC cost. As a result, finding more cost-effective biodiesel production methods is critical to the industry’s economic viability. Regulators and policymakers involved in biodiesel production projects may find the framework useful in obtaining a compromise solution for socio-economic goals based on their preferences.
A Grey-Fuzzy Programming Approach towards Socio-Economic Optimization of Second-Generation Biodiesel Supply Chains
Mohammad Kanan (author) / Muhammad Salman Habib (author) / Anam Shahbaz (author) / Amjad Hussain (author) / Tufail Habib (author) / Hamid Raza (author) / Zaher Abusaq (author) / Ramiz Assaf (author)
2022
Article (Journal)
Electronic Resource
Unknown
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