Optimised redesign of reverse logistics network with multi-level capacity choices for household appliances
Optimised redesign of reverse logistics network with multi-level capacity choices for household appliances
复制标题
家电逆向物流网络优化再设计，多级产能选择
DOI：
10.1080/00207543.2021.1967499
复制
发表时间：
2021-09
影响因子：
9.2
通讯作者：
Zhibin Jiang
中科院分区：
文献类型：
--
作者：
Ada Che;Jieyu Lei;Zhibin Jiang
逆向物流网络将报废产品重新引入再制造，对可持续发展和环境保护具有重要意义。在本文中，我们调查了目前在中国的家电逆向物流网络，并重新设计了一个新的网络，引入必要的设施：拆卸中心和三种类型的再制造工厂，以提高回收率。提出了一个具有多级能力选择的混合整数线性规划模型，用于确定拆卸中心和再制造工厂的位置和能力。一个有效的分解和扩展启发式求解模型。使用一个真实的案例对重新设计的网络进行了评估。结果表明，回收率大大提高了新的网络中，几乎所有有用的材料可以回收，而在传统的网络中，只有金属有效地回收。模型参数的敏感性分析进行了田口方法，以确定其对回收决策的影响。所提出的算法进一步评估使用一组随机生成的实例。结果表明，该算法可以在较短的时间内得到高质量的解。通过对生成的实例进行参数敏感性分析，提出了算法的最佳配置。
Reverse logistics networks reintroduce end-of-life products to remanufacturing, which is significant for sustainable development and environmental protection. In this paper, we investigate the current reverse logistics network of household appliances in China and redesign a new network that introduces necessary facilities: disassembly centres and three types of remanufacturing plants to improve recycling rates. A mixed-integer linear programming model with multi-level capacity choices is proposed to determine the locations and capacities for disassembly centres and remanufacturing plants. An efficient decomposition-and-expansion heuristic is developed to solve the model. The redesigned network is evaluated using a real case. The results indicate that the recycling rate is largely improved by the new network in which almost all useful materials can be recycled, whereas, in the traditional network, only metals are efficiently recycled. A sensitivity analysis of model parameters is conducted using the Taguchi method to identify their effects on recycling decisions. The proposed algorithm is further evaluated using a set of randomly generated instances. The results show that the algorithm can yield high-quality solutions within a short time. The best configuration of the algorithm is suggested via sensitivity analysis of parameters using the generated instances.
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