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.

本研究提出了一个多目标数学模型来设计一个以可持续发展目标为重点的天然气供应链网络。基于所提出模型的经济目标，尝试最小化整个供应链成本。环境目标将温室气体排放量、电力消耗、气体消耗、水消耗和废水产生量降至最低。社会目标还考虑平衡就业、平衡经济发展、员工福利、员工安全、客户成本风险和运营环境风险。由于现实世界中的参数是不确定的，很少能精确估计，所以考虑了模型参数的不确定性。四阶段求解方法用于求解所提出的模型。在第一步中，在地理信息系统 (GIS) 软件中使用最佳最差方法对图层进行加权。第二步，在GIS软件中确定建议的城门站。第三步，采用稳健的可能性规划方法处理参数的不确定性。最后，在第四步中，使用 Torabi-Hassini 方法将多目标模型转化为单目标模型。为了评估所提出模型的效率，对法尔斯省天然气公司进行了真实案例研究。数值结果证实了所提出模型的有效性，揭示了与模型参数相关的不确定性不可忽视，因为系统成本在不确定性下受到显着影响。而且，