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Robust Optimization Model for Remanufacturing System in Uncertain Reverse Logistics Environment

机译:不确定反向物流环境中再制造系统的鲁棒优化模型

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The remanufacturing process of reusable parts in uncertain reverse logistics environment is considered. An existing framework for remanufacturing system is adopted. In this framework, the manufacturer has two alternatives for supplying parts: either ordering the required parts to external suppliers or overhauling returned products and bringing them back to 'as new' conditions. The numbers of returned products are uncertain and can be described as a scenario set with certain probability. By using the approach of robust optimization based on scenario analysis, a robust optimization model is constructed to maximize the total cost savings by optimally deciding the quantity of parts to be processed at each remanufacturing facilities, the number of purchased parts from subcontractor. The results of a numerical example show that the model we proposed is both solution-robust and model-robust.
机译:考虑了不确定逆向物流环境中可重复使用部件的再制造过程。采用现有的再制造系统框架。在此框架中,制造商有两种供应部件的替代方案:订购所需的部件到外部供应商或检修退回的产品,并将其恢复为“作为新”条件。返回产品的数量不确定,可以描述为具有某些概率的场景。通过使用基于场景分析的鲁棒优化方法,构造了一种强大的优化模型,以通过最佳地确定要在每个再制造设施中处理的部件数量,分包商的购买部分的数量来最大化总成本节约。数字示例的结果表明,我们提出的模型是解决方案 - 稳健和模型稳健。

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