A Lagrangian relaxation approach for algae-based biofuel supply chain network design under uncertainty and pricing issue

被引：0

作者：

Arabi, Mahsa ^{[1
]}

Yaghoubi, Saeed ^{[1
]}

机构：

[1] School of Industrial Engineering, Iran University of Science and Technology, Tehran, Narmak

来源：

Environmental Science and Pollution Research | 2024年 / 31卷 / 55期

关键词：

Algal biofuel supply chain; Data envelopment analysis; Multi-objective; Network design; Stochastic programming; Variable demand;

D O I：

10.1007/s11356-024-35428-7

中图分类号：

学科分类号：

摘要：

Biofuel has gained significant attention as a potential source to meet fuel demands instead of fossil fuel. The price of biofuel and alternative fuel have a considerable impact on biofuel demand. Thus, it is important to design a biofuel supply chain network that incorporates the biofuel price into an elastic demand. More precisely, a variable demand, including customer importance level (to the environment), biofuel price, and substituted fuel price, is considered in this research. Furthermore, this research presents a bi-objective mixed-integer quadratic formulation that aims to maximize the total profit of the supply chain and carbon absorption in harvesting areas. The problem is solved by the ε-constraint and lagrangian relaxation methods due to its complexity. Moreover, substituted fuel price uncertainty is addressed by two-stage stochastic programming. Finally, a real case study utilizing the data envelopment analysis approach is applied to assess the efficiency and currency of the addressed model. Several consequences are illustrated in the case study, such as rich areas for exporting algae, suggesting hub locations for biofuel production, etc. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

引用

页码：64048 / 64068

页数：20

共 59 条

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