Bioethanol sustainable supply chain design
A multi-attribute bi-objective structure
Siamak Kheybari (University of Cambridge)
Mansoor Davoodi Monfared (Helmholtz Zentrum Dresden Rossendorf, Institute for Advanced Studies in Basic Sciences, Zanjan)
Amirhossein Salamirad (University of British Columbia)
J Rezaei (TU Delft - Transport and Logistics)
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Abstract
To design a bioethanol supply chain, along with the transportation and operational costs, it is vital to consider more factors categorized into three sustainability pillars (i.e. economy, social and environment). In this paper, to develop a mathematical model for bioethanol supply chain (BSC), we propose a two-phase methodology; in the first phase, using a sustainable framework of attributes contributing to the facility location selection in the BSC network, we calculate the sustainability score of alternatives through employing the best-worst method (BWM). Then, considering the results of the multi-attribute step as the parameters of an objective function called the sustainability value function, we develop a bi-objective multi-level bioethanol supply chain model. To solve the proposed model, a Nested bi-objective Optimization Genetic Algorithm (NbOGA) is introduced in this research. Finally, we evaluate the performance of the presented BSC model and the algorithm for a real-world problem. The results show that using the proposed structure, both sustainability attributes and transportation costs are appropriately satisfied in the BSC network.
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