发表机构
The University of British Columbia（不列颠哥伦比亚大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文针对复杂供应链中的牛鞭效应，提出通过分配订单、缩短前置时间和调整订货增益来最小化最坏情况放大的网络设计方法，实验表明优化设计显著降低放大并增强网络鲁棒性。
AI 中文摘要
本文研究了供应链网络中的牛鞭效应，即需求波动沿上游方向被放大为更大的订单波动。在该网络中，每家企业通过具有不同前置时间（lead times）的路径向多家供应商订货。我们证明，在有向无环网络上，从需求到订单的每个响应都可以表示为沿各路径的节点响应乘积之和，因此网络的稳定性及其稳定裕度由各个节点的稳定性及其稳定裕度决定；同时，将订单分散到不同长度的路径上的节点，可以获得额外的裕度，并可用于提高增益和加快响应速度。随后，我们通过选择每家企业如何在其供应商之间分配订单、缩短哪些路径的前置时间以及设定每家企业的订货增益，来最小化网络的最坏情况放大，其中梯度通过每个需求节点和频率的一次伴随传递（adjoint pass）计算。在一个14个城市的网络上，优化后的设计比成本最小化路由的放大低20分贝，比使用相同预算缩短最长路径的设计低17分贝，并且网络连通性优于两者。因此，放大是路由和延迟的属性，而不仅仅是订货策略的属性，针对放大进行设计还能使网络在失去一条路径时更加稳健。
英文摘要
This paper studies the bullwhip effect, the amplification of demand fluctuations into larger order fluctuations upstream, in supply chain networks where each firm orders from several suppliers over routes with different lead times. We show that on a directed acyclic network every response from demand to orders is a sum over paths of products of nodal responses, so that the stability and stability margins of the network are determined by those of its individual nodes, and that a node which splits its orders across routes of different lengths gains margin it can spend on a higher gain and a faster response. We then minimize the worst-case amplification of the network by choosing how each firm splits its orders among its suppliers, which route lead times to shorten, and each firm's ordering gain, with gradients from one adjoint pass per demand node and frequency. On a 14-city network the optimized design amplifies 20~dB less than cost-minimal routing and 17~dB less than a design that shortens the longest routes with the same budget, and is better connected than either. Amplification is therefore a property of routing and delay, not only of the ordering policy, and designing against it also makes the network more robust to a lost route.
Comments11 pages, 10 figures
