Designing and planning a bioethanol supply chain network under uncertainty using a data-driven robust optimization model under disjunctive uncertainty sets

Purpose: Most research in the field of designing and planning bioethanol supply chains has been based on deterministic models, which do not consider dynamic environmental conditions and thus do not provide reliable outputs. Classic robust models did not have this weakness, but due to their excessive...

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Bibliographic Details
Main Authors: Farzaneh MansooriMooseloo, Maghsoud Amiri, Mohammad Taghi Taghavi Fard, Mostafa Hajiaghaei-Keshteli
Format: Article
Language:fas
Published: Ayandegan Institute of Higher Education, Tonekabon, 2024-08-01
Series:تصمیم گیری و تحقیق در عملیات
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Online Access:https://www.journal-dmor.ir/article_199979_50d6ea02d6e97890f465b830323094e0.pdf
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Summary:Purpose: Most research in the field of designing and planning bioethanol supply chains has been based on deterministic models, which do not consider dynamic environmental conditions and thus do not provide reliable outputs. Classic robust models did not have this weakness, but due to their excessive conservatism, they increased supply chain costs, making them unattractive to investors. Therefore, the aim of this study is to design and optimize the biomass-to-bioethanol supply chain network using data-driven robust optimization methods and disjunctive uncertainty sets.Methodology: The methodology of this study is a multi-methodology approach based on mathematical modeling and machine learning algorithms. Initially, uncertainty sets for the non-deterministic model parameter were created using K-means and SVC methods. Then, a data-driven optimization model was designed to optimize the biomass-to-bioethanol supply chain network, addressing the issues of previous classic approaches.Findings: The findings of this study are presented in two categories: strategic and operational decisions. The strategic section focuses on determining the optimal locations for biomass cultivation, preprocessing centers, and refineries. In the operational section, the optimal amounts of biomass sent to preprocessing centers and refineries were determined.Originality/Value: This study, by producing robust solutions without the conservatism of traditional robust optimization approaches, can significantly attract public and private sector investors. Additionally, using a three-objective model based on a sustainable development approach that simultaneously considers economic, social, and environmental components, enhances the comprehensiveness of this research, providing more realistic and detailed results.
ISSN:2538-5097
2676-6159