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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:政府补贴下逆向物流网络设计的新型两阶段随机模型及低碳排放要求

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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,越来越多的公司纳入其供应链设计中的反向物流决策,以应对强制国际和国家立法,提高资源效率和公共形象。本文调查了在政府补贴和低碳排放要求下设计单期多产品多级逆向物流系统的新随机优化模型。为了解决随机优化问题,提出了一种改进的多标准情景的方法,以最大化利润产生,同时提高不确定性下决策的稳定性。使用若干数值实验测试了模型和解决方案方法,并获得了基于碳排放要求,政府补贴,规模经济和系统灵活性的管理洞察。

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