Magnified resource consumption and depletion of natural resources calls for non-flexible or strict regulations and penalties on industrial operations, increased rate of processing and reuse of waste material as a substitute for raw material and political and legal interventions at global scale. Product recovery involves reuse, repair, refurbishing, remanufacturing and materials recycling, requires an efficient network design known as reverse logistic network and offers economical benefits in terms of fewer procurement of raw material, inventory management and less disposal. In current study, a mixed integer linear programming model designed on a multi-stage reverse logistics network for product recovery is proposed which considers different recovery options-product remanufacturing, component reprocessing and material recycling for sustainable outcomes. The model is designed to find optimal solutions for fulfilling demand and revenue needs by focusing on strategic locations for collection centers, reprocessing centers, remanufacturing plants and transportation options and simultaneously achieving sustainability goals. The model is applied on an Indian based manufacturing unit of a Saudi Arabian Industrial Air conditioner manufacturing organization and the case is presented here. The model is converted into a multi-objective programming model in accordance with the importance of each objective suiting the business needs. All relevant objective functions are evaluated using BWM, AHP and FAHP methods to obtain weights for integration into a fuzzy linear programming model which eventually provides three separate results. The model applied has originality and uniqueness for applications to solve multi-objective problems under uncertain environment and tends to strike a balance between economic and environmental objectives. The study provides for a base for further scope covering uncertainty about the amount and quality of returned products and even can be implemented by practitioners and academics for making a significant contribution in improving the efficiency of supply chains.

中文翻译：

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工业空调制造公司设计可持续供应链的逆向物流优化：模糊混合多准则决策方法

扩大的资源消耗和自然资源的枯竭要求对工业运营采取不灵活或严格的规定和惩罚，提高废料的加工和再利用率以替代原材料，并在全球范围内进行政治和法律干预。产品回收涉及再利用，维修，翻新，再制造和材料回收，需要有效的网络设计（称为逆向物流网络），并且在减少原材料采购，库存管理和处置方面提供了经济利益。在当前的研究中，提出了一种在多阶段逆向物流网络上设计的用于产品回收的混合整数线性规划模型，该模型考虑了不同的回收选项-产品再制造，组件再加工和材料回收以实现可持续的结果。该模型旨在通过针对收集中心，后处理中心，再制造工厂和运输选择的战略位置并同时实现可持续发展目标来找到满足需求和收入需求的最佳解决方案。该模型应用于沙特阿拉伯工业空调制造组织在印度的制造部门，并在此处介绍了该案例。根据适合业务需求的每个目标的重要性，将模型转换为多目标编程模型。使用BWM，AHP和FAHP方法对所有相关目标函数进行评估，以获得权重以集成到模​​糊线性规划模型中，该模型最终提供了三个单独的结果。所应用的模型对于解决不确定环境下的多目标问题具有独特性和独特性，并倾向于在经济和环境目标之间取得平衡。该研究为进一步涵盖退货产品的数量和质量的不确定性提供了基础，甚至可以由从业者和学者实施，以对提高供应链效率做出重大贡献。