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Integration of logistics outsourcing decisions in a green supply chain design: A stochastic multi-objective multi-period multi-product programming model

机译:在绿色供应链设计中整合物流外包决策:随机多目标多周期多产品编程模型

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This paper develops a programming model, which combines logistics outsourcing decisions with some strategic Supply Chains' planning issues, such as the Security of supplies, the customer Segmentation, and the Extended Producer Responsibility. The purpose is to minimize both the expected logistics cost and the Green House Gas (GHG) emissions of the Supply Chain (SC) network, in the context of business environment uncertainty. First, we define a general structure of the closed-loop SC. Second, we provide constructive models to roughly estimate the insourcing and outsourcing logistics costs, and their corresponding GHG emissions. Third, we establish a stochastic plan based on a scenarios approach to capture the uncertainty od demand, capacity of facilities, quantity and quality of returns of used products, and the transportation, warehousing, and reprocessing costs. Fourth, we suggest a programming model, and an algorithm based on the Epsilon-constraint method to solve it. The result is a set of optimal non-dominant green SC configurations, which provide the decision' makers with optimal levels of logistics outsourcing integration within a decarbonized Supply Chain, before any further low-carbon investment. (C) 2016 Elsevier B.V. All rights reserved.
机译:本文开发了一种编程模型,该模型将物流外包决策与一些战略供应链的计划问题相结合,例如供应安全,客户细分和生产者扩展责任。目的是在商业环境不确定的情况下,将预期的物流成本和供应链(SC)网络的温室气体(GHG)排放量降至最低。首先,我们定义闭环SC的一般结构。其次,我们提供了建设性的模型,可以粗略估算内购和外购物流成本及其相应的温室气体排放量。第三,我们基于情景方法建立随机计划,以捕获需求的不确定性,设施的容量,二手产品的退货的数量和质量以及运输,仓储和后处理成本。第四,我们提出了一种编程模型,以及一种基于Epsilon约束方法的算法来解决该问题。结果是一组最佳的非主导绿色供应链配置,为决策者提供了在脱碳供应链内进行最佳的物流外包整合水平,然后再进行任何低碳投资。 (C)2016 Elsevier B.V.保留所有权利。

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