Shafiee Roudbari Erfan, Fatemi Ghomi S M T, Eicker Ursula
Department of Building, Civil and Environmental Engineering, Concordia University, Montreal, QC Canada.
Department of Industrial Engineering, Amirkabir University of Technology, Tehran, 1591634311 Iran.
Environ Dev Sustain. 2023 Feb 1:1-32. doi: 10.1007/s10668-023-02953-3.
The global population continues to grow, which expands demand for raw materials. Meanwhile, governments are developing circular economy strategies within cities and their industries. A circular economy utilizes refurbishing, reusing, remanufacturing, and repairing of products and materials. For companies, this involves to set targets and to rethink their supply chain. This paper seeks to model an exhaustive multi-echelon closed-loop supply chain (CLSC) network. This network functions within uncertainty, and the model optimizes three different objectives. The first objective function maximizes the network's profit; the second objective function minimizes network emissions. The last objective function maximizes job positions created by the network. Optimizing three contradicting objectives is a problem, so an augmented epsilon constraint method is applied to improve the model. Given the rise of fast fashion in developed countries, this model is used in the clothing industry in Montreal, Canada. The model includes three scenarios over five years with two types of products. The result shows the attractiveness of such a network for companies looking for profit, sustainability, and entrepreneurship in the garment industry.
全球人口持续增长，这扩大了对原材料的需求。与此同时，各国政府正在城市及其产业中制定循环经济战略。循环经济利用产品和材料的翻新、再利用、再制造和修复。对于企业来说，这涉及设定目标并重新思考其供应链。本文旨在构建一个详尽的多梯队闭环供应链（CLSC）网络模型。该网络在不确定性环境下运行，且该模型优化三个不同目标。第一个目标函数使网络利润最大化；第二个目标函数使网络排放最小化。最后一个目标函数使网络创造的就业岗位最大化。优化三个相互矛盾的目标是个难题，因此应用增强型ε约束方法来改进该模型。鉴于发达国家快时尚的兴起，此模型应用于加拿大蒙特利尔的服装行业。该模型包含针对两类产品的五年内的三种情景。结果表明，这样一个网络对于在服装行业寻求利润、可持续性和创业机会的公司具有吸引力。
