Optimal design of a sustainable natural gas supply chain network under uncertainty

被引:25
作者
Bazyar, Arash [1 ]
Zarrinpoor, Naeme [1 ]
Safauian, Amir [2 ]
机构
[1] Shiraz Univ Technol, Dept Ind Engn, Shiraz, Iran
[2] Fars Prov Gas Co, Gas Measuring & Calculat, Shiraz, Iran
关键词
Supply chain design; Natural gas; Sustainability; Uncertainty; Robust optimization; DISTRIBUTION-SYSTEM; OPTIMIZATION; MODEL;
D O I
10.1016/j.cherd.2021.09.006
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
This study proposes a multi-objective mathematical model to design a natural gas supply chain network with a focus on sustainable development goals. Based on the economic objective of the proposed model, an attempt is made to minimize the whole supply chain costs. The environmental objective minimizes the amount of greenhouse gas emissions, electricity consumption, gas consumption, water consumption, and wastewater generation. The social objective also considers balanced employment, balanced economic development, employee welfare, employee safety, customers cost risk, and operational environment risk. Because parameters in the real world are uncertain and can rarely be estimated precisely, the uncertainty of the model parameters is taken into account. A four-stage solution approach is used to solve the proposed model. In the first step, the best-worst method is used to weight the layers in geographic information system (GIS) software. In the second step, the suggested city gate stations are determined in GIS software. In the third step, a robust possibilistic programming method is used to deal with the uncertainty of the parameters. Finally, in the fourth step, the Torabi-Hassini method is used to transform the multi-objective model into a single-objective one. In order to evaluate the efficiency of the proposed model, a real case study is conducted on Fars Province Gas Company. Numerical results confirm the efficiency of the proposed model, revealing that the uncertainty associated with the model parameters cannot be ignored because system costs are significantly affected under uncertainty. Moreover, the capacity parameter of the suggested city gate station could have a significant effect on system costs while the largest share of supply chain costs is related to transmission fixed costs. (c) 2021 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:60 / 88
页数:29
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