Shipment Consolidation and Synchronization of Inbound-Outbound Supply Chain Flows

进出供应链流程的装运整合和同步

• 批准号: RGPIN-2019-06207
• 负责人: Bookbinder, James
• 金额: $ 1.89万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=758138
• 关键词: Shipment; Consolidation; Synchronization; Inbound; Outbound

A set of suppliers each furnish one or more products to a group of retailers. Direct shipment, from each origin to every destination, is often inefficient. We study, therefore, the distribution consolidation problem, in which products from multiple origins to the various destinations will be transported via a consolidation terminal. The latter is termed "node O" of the supply chain.    As in industry, the flows in this many-to-many supply chain (many suppliers, many retailers) are coordinated by a 3PL (third party logistics provider). We will develop an optimization model, and several extensions, to synchronize these supply-chain flows.    The 3PL does not operate its own transportation assets. Rather, it acts as a broker, to arrange shipments via public carriers, of the goods from each supplier that are ordered by each retailer. Based on demand forecasts for the products, the 3PL commits (signs contracts) for a number of "transportation options." Each such supplier option is a combination of a capacity and an arrival time at the consolidation center O. Similarly, customer transportation options each have a given capacity and time of dispatch from O. Naturally, every option has an associated cost.    The demands for each product can be estimated, but because of randomness in those demands, the amount of required transportation capacity and its timing are uncertain. We will thus model this situation as a two-stage stochastic programming problem. The first stage decisions are the assignment of shipments, inbound to O and outbound from there, to respective transportation options. When the actual demands become known, the second stage decisions involve assignment of loads to spot-market carriers, to the degree necessary.    We will develop an efficient solution algorithm for this problem. Building on already-existing relationships with a supplier and a 3PL, we will refine the basic model as above, and implement it at one or more partner firms. The team of student researchers and I will then expand the applicabili

因此，一组供应商分别向一组零售商提供一种或多种产品，从每个原产地到每个目的地的直接运输通常效率低下。后者被称为供应链的“节点 O”。在工业中，这个多对多供应链（许多供应商、许多零售商）中的流程由 3PL（第三方）协调。物流供应商）。将开发一个优化模型和一些扩展，以同步这些供应链流程。 ​ 3PL 不运营自己的运输资产，而是充当经纪人，通过公共承运商安排来自每个供应商的货物运输。根据每个零售商订购的产品需求预测，3PL 承诺（签署合同）许多“运输选项”。每个此类供应商选项都是容量和到达整合中心的时间的组合。 。同样，每个客户运输选项都有给定的容量和从 O 发货的时间。当然，每个选项都有相关的成本。​每种产品的需求是可以估计的，但由于这些需求的随机性，所需的运输容量。因此，我们将这种情况建模为两阶段随机规划问题，即当实际需求已知时，将进货到 O 以及从 O 出站的货物分配给相应的运输选项。 ，第二阶段决策涉及负载分配​我们将在与供应商和 3PL 的现有关系的基础上，针对该问题开发一种有效的解决算法，完善上述基本模型，并一次性实施。或更多合作伙伴公司，然后我和学生研究人员团队将扩大其适用范围。