Bioethanol sustainable supply chain design: A multi-attribute bi-objective structure

Siamak Kheybari*, Mansoor Davoodi Monfared, Amirhossein Salamirad, Jafar Rezaei

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

2 Citations (Scopus)
20 Downloads (Pure)

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.
Original languageEnglish
Article number109258
JournalComputers and Industrial Engineering
Volume180
DOIs
Publication statusPublished - 2023

Keywords

  • best-worst method (BWM)
  • Bi-objective optimization
  • Bioethanol supply chain
  • Genetic algorithm
  • Sustainability index

Fingerprint

Dive into the research topics of 'Bioethanol sustainable supply chain design: A multi-attribute bi-objective structure'. Together they form a unique fingerprint.

Cite this