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A new two-stage stochastic model for reverse logistics network design under government subsidy and low-carbon emission requirement

机译:政府补贴和低碳排放下逆向物流网络设计的两阶段随机模型

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Nowadays, increasing number of companies incorporates the reverse logistics decisions into their supply chain design in order to cope with the enforced international and national legislation and improve the resource efficiency and public image. This paper investigates a new stochastic optimization model for designing a single-period multi-product multi-level reverse logistics system under government subsidy and low-carbon emission requirement. In order to resolve the stochastic optimization problem, a modified multi-criteria scenario-based approach is proposed to maximize the profit generation while simultaneously improve the stability of the decision-making under uncertainty. The model and solution method are tested with several numerical experiments, and managerial insights are obtained with respect to the carbon emission requirement, governmental subsidy, economy of scale, and system flexibility.
机译:如今,越来越多的公司将逆向物流决策纳入其供应链设计中,以应对强制执行的国际和国家法规并提高资源效率和公众形象。本文研究了一种在政府补贴和低碳排放需求下设计单周期多产品多级逆向物流系统的随机优化模型。为了解决随机优化问题,提出了一种基于多准则场景的改进方法,可以在最大程度上提高利润产生的同时,提高不确定性条件下决策的稳定性。该模型和求解方法通过数个数值实验进行了测试,并且在碳排放要求,政府补贴,规模经济和系统灵活性方面获得了管理方面的见识。

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