Shipment Consolidation and Synchronization of Inbound-Outbound Supply Chain Flows

一组供应商各自向一组零售商提供一种或多种产品。从每个产地到每个目的地的直接运输往往效率低下。因此，我们研究了配送整合问题，其中产品从多个原产地到不同目的地将通过一个整合终端进行运输。后者被称为供应链的“节点O”。****与工业中一样，这个多对多供应链（许多供应商，许多零售商）中的流程由第三方物流提供商（3PL）协调。我们将开发一个优化模型和几个扩展，以同步这些供应链流。****第三方物流不经营自己的运输资产。相反，它扮演的是一个经纪人的角色，通过公共承运人安排每个零售商订购的每个供应商的货物的运输。根据对产品的需求预测，第三方物流承诺（签署合同）许多“运输选项”。每个这样的供应商选项都是容量和到达整合中心o的时间的组合。类似地，每个客户的运输选项都有给定的容量和从o发送的时间。****每种产品的需求可以估计，但由于这些需求的随机性，所需运输能力的数量及其时间是不确定的。因此，我们将这种情况建模为一个两阶段随机规划问题。第一阶段的决策是将货物分配给各自的运输选项，即从O站到O站和从O站到出站。当实际需求已知时，第二阶段的决策涉及到在必要的程度上将负载分配给现货市场承运商。****我们将为这个问题开发一个有效的求解算法。在与供应商和第三方物流公司已有关系的基础上，我们将完善上述基本模型，并在一个或多个合作伙伴公司中实施。然后，由学生研究人员和我组成的团队将在第2-5年扩展模型的适用性。这些扩展包括在模型中加入需求预测；随着前期实际需求的了解，对这些预测的修正；以及在“滚动时间范围”（而不是固定的、静态的时间段）中适应和使用模型。****我们提出的研究的理论贡献：****将上述问题作为装运整合问题的多产品解决方案进行增强****对供应商管理库存的扩展，其中第三方物流管理特定零售商的某些产品的库存****在位置建模理论中包含装运整合。（应该有多少个合并终端，它们应该设在哪里？）****该研究项目将培养3名博士，3名硕士。5微克。他们将获得优化建模和软件方面的经验，并将成为研究出版物的共同作者。*********

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 applicability of the model in years 2-5. Among the extensions are the inclusion of demand forecasting within the model; the revision of those forecasts as actual demands of early periods become known; and adaptation and use of the model in a “rolling time horizon” (rather than a fixed, static time period).**** Theoretical contributions of our proposed research:**** Enhancing the above as a multi-product solution of the shipment-consolidation problem**** An extension to Vendor Managed Inventory, in which the 3PL manages the stocks of certain products at particular retailers**** The inclusion of shipment consolidation within the theory of location modelling. (How many consolidation terminals should there be, and where should they be located?)**** This research program will train 3 PhD, 3 MASc. and 5 UG. They will gain experience in optimization modeling and software, and will be co-authors of research publications.*********