Department of Industrial Engineering, Yazd University, Yazd, Iran, and Behineh Gostar Sanaye Arman, Tehran, Iran.
Department of Mechanical, Industrial and Aerospace Engineering, Concordia University, Montreal, Canada.
Environ Sci Pollut Res Int. 2022 Oct;29(46):70285-70304. doi: 10.1007/s11356-022-20713-0. Epub 2022 May 19.
The viable closed-loop supply chain network (VCLSCND) is a new concept that integrates sustainability, resiliency, and agility into a circular economy. We suggest a hybrid robust stochastic optimization by minimizing the weighted expected, maximum, and entropic value at risk (EVaR) of the cost function for this problem. This form considers robustness against demand disruption. Finally, CLSC components are located, and quantity flows are determined in the automotive industry. The results show that the VCLSCND cost is less than not considering viability and has a - 0.44% gap. We analyze essential parameters. By increasing the conservative coefficient, confidence level, and the scale of the main model, decreasing the allowed maximum energy, the cost function, time solution, and energy consumption grow. We suggested applying the Fix-and-Optimize algorithm for producing an upper bound for large-scale. As can be seen, the gap between this algorithm and the main problem for cost, energy, and time solution is approximately 6.10%, - 8.28%, and 75.01%.
可行闭环供应链网络（VCLSCND）是一个将可持续性、弹性和敏捷性集成到循环经济中的新概念。我们建议通过最小化成本函数的加权期望、最大和熵风险价值（EVaR）来对此问题进行混合鲁棒随机优化。这种形式考虑了对需求中断的稳健性。最后，在汽车行业中定位了 CLSC 组件，并确定了数量流。结果表明，不考虑可行性的 VCLSCND 成本较低，差距为-0.44%。我们分析了重要参数。通过增加保守系数、置信水平和主模型的规模，降低允许的最大能量，可以增加成本函数、时间解决方案和能源消耗。我们建议应用 Fix-and-Optimize 算法来为大规模生产提供上限。可以看出，该算法与主问题在成本、能源和时间解决方案方面的差距约为 6.10%、-8.28%和 75.01%。
