Supply Chain Logistics Problem Dataset

Dataset is divided into 7 tables, one table for all orders that needs to be assigned a route – <i>OrderList</i> table, and 6 additional files specifying the problem and restrictions. For instance, the <i>FreightRates</i> table describes all available couriers, the weight gaps for each individual lane and rates associated. The <i>PlantPorts</i> table describes the allowed links between the warehouses and shipping ports in real world. Furthermore, the <i>ProductsPerPlant</i> table lists all supported warehouse-product combinations. The V<i>miCustomers</i> lists all special cases, where warehouse is only allowed to support specific customer, while any other non-listed warehouse can supply any customer. Moreover, the <i>WhCapacities</i> lists warehouse capacities measured in number of orders per day and the <i>WhCosts</i> specifies the cost associated in storing the products in given warehouse measured in dollars per unit.<br>Order ID is ID of the order made by the customer, product ID is the specific product ID customer ordered.<br>"tpt_day_cnt" in the FrieghtRates table means transportation day count, i.e. estimated shipping time. <br>WhCapacities correspond to the number of orders. For example, let's say Customer 1 requests 10 units of X, Customer 2 requests 20 units of Y. The total number of orders is 2, thus total capacity in "whCapacity" is 2.<br><br>WhCapacities table is the maximum number of orders that can be processed per each plant, it is not dependant on specific products.<br><br>The OrderList contains historical records of how the orders were routed and demand satisfied. The whCapacities and rest of the tables are the current state constraints of the network. Thus, we can calculate the costs of historical network and also optimize for the new constraints. <br><br>In order to build Linear Programming (LP) model, you would take the following from the OrderList: the product ID that needs to be shipped, the destination port, unit quantity (for cost) and unit weight (for weight constraints). And then use the limits of those constraints from other tables.<br><b>Questions: </b>There is a Carrier V44_3 in OrderList table, but it is missing in the FreightRates table? V44_3 is a carrier that was historically used for supplying given demand, but since it has been discontinued and therefore do not appear in the Freight Rates List. Also, all of the V44_3 instances are CRF - i.e. customer arranges their own shipping and hence cost is not calculated either way. <br>

本数据集共分为7张数据表，其中一张为**订单列表（OrderList）**，用于存储所有需要规划配送路线的订单；其余6张附加文件用于明确问题背景与各类约束条件。
例如，**运价表（FreightRates）**描述了所有可用承运商、各运输线路对应的重量区间及关联运价。**工厂港口关联表（PlantPorts）**记录了现实场景中仓库与货运港口之间的合法连接关系。**工厂-产品适配表（ProductsPerPlant）**列出了所有受支持的仓库-产品组合。**供应商管理库存客户表（VmiCustomers）**列明了所有特殊场景：仅允许特定仓库为指定客户供货，未在本表中列明的仓库则可向任意客户供货。此外，**仓库产能表（WhCapacities）**以每日可处理订单数量为单位，记录各仓库的产能上限；**仓库存储成本表（WhCosts）**以每单位美元为计价标准，明确在指定仓库存储产品所需承担的单位存储成本。

订单ID为客户所下订单的唯一标识，产品ID则指代客户订购的特定产品的编号。
运价表（FreightRates）中的“tpt_day_cnt”字段表示运输天数，即预估的货运时长。
仓库产能表（WhCapacities）中的产能以订单数量为统计单位。举例而言，若客户1订购10单位的X产品，客户2订购20单位的Y产品，总订单数为2，则仓库“whCapacity”字段对应的总产能应至少为2。
仓库产能表（WhCapacities）中记录的是各仓库每日可处理的最大订单数，与具体产品品类无关。
订单列表（OrderList）存储了历史订单的配送路径规划记录与需求满足情况，而仓库产能表及其余数据表则代表当前物流网络的约束条件。据此，既可计算历史物流网络的运营成本，也可针对新约束条件开展优化工作。
若要构建线性规划（Linear Programming, LP）模型，需从订单列表（OrderList）中提取以下信息：待运输产品的ID、目的港口、单位产品数量（用于成本核算）以及单位产品重量（用于重量约束校验），再结合其他数据表中的约束限值开展建模。

**问题：** 订单列表（OrderList）中存在承运商V44_3，但该承运商未在运价表（FreightRates）中出现？原因在于，V44_3是历史上曾用于供货的承运商，但目前已停止运营，因此未出现在当前可用承运商列表中。此外，所有V44_3的运输实例均为CRF模式——即由客户自行安排运输，因此无需计算此类运输的相关成本。