A Robust Possibilistic Bi-Objective Mixed Integer Model for Green Biofuel Supply Chain Design under Uncertain Conditions

Hossein Savoji, Seyed Meysam Mousavi (), Jurgita Antucheviciene and Miroslavas Pavlovskis
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Hossein Savoji: Department of Industrial Engineering, Shahed University, Tehran 3319118651, Iran
Seyed Meysam Mousavi: Department of Industrial Engineering, Shahed University, Tehran 3319118651, Iran
Jurgita Antucheviciene: Department of Construction Management and Real Estate, Vilnius Gediminas Technical University, 10223 Vilnius, Lithuania
Miroslavas Pavlovskis: Department of Construction Management and Real Estate, Vilnius Gediminas Technical University, 10223 Vilnius, Lithuania

Sustainability, 2022, vol. 14, issue 20, 1-16

Abstract: In recent years, concerns regarding issues such as climate change, greenhouse gas emissions, fossil reserve dependency, and petroleum price fluctuation have led countries to focus on renewable energies. Meanwhile, in developing countries, designing an appropriate biofuel supply chain network regarding environmental competencies is an important problem. This paper presents a new bi-objective mixed integer mathematical model aiming to minimize CO 2 emission and total costs in the process of the biofuel supply chain, creating a suitable green supply chain network. In this respect, CO 2 emission and biofuel demand are regarded as uncertain data to address the real complex cases. Moreover, the SAUGMECON approach was implemented to construct a single objective model, and the obtained Pareto optimal points were depicted and analyzed. Thereby, a robust possibilistic programming approach was implemented to the proposed model to handle existing imprecise data. Furthermore, the applicability and performance of the proposed model were demonstrated based on an experimental example. In this respect, the obtained results from the proposed robust possibilistic programming model were compared with its crisp form to show the robustness and reliability of the proposed uncertain mathematical model.

Keywords: bi-objective mixed integer programming; renewable energy; green; robust possibilistic approach; biofuel supply chain network design (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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