Supply chain consolidation and cooperation in the agriculture industry

Freight transportation supports the economic activity of the United States. Trucking is the most frequently used method of transportation in the agriculture industry. The majority of suppliers in the agriculture industry are small farmers with little demand. We investigate a supply chain system with small farmers. Two models are considered in this research for the shipping of perishable goods. Both models consider a transportation network with direct shipping modes to and from a single consolidation center. We represent perishability as a hard constraint on the total time products are allowed to stay at the consolidation center. In the first model, we assume inventory costs are negligible, and only consider transportation costs. We develop a consolidation heuristic that is efficient and easy‐to‐implement in practice. The consolidation strategy exploits economies of scale from three shipping methods: full truckload rates, less‐than‐truckload rates, and courier rates. A dynamic programming model is developed to calculate an optimal solution. Both solution approaches solve the deterministic and stochastic cases of the direct shipping consolidation model with multiple suppliers and seasonal demand. The second model adds inventory costs, a soft constraint for perishability, to the first model. A dynamic programming algorithm and a heuristic that calculates the trade‐off between shipping and holding inventory are developed. Numerical results show that the heuristic performs well for high inventory costs. However, if the inventory costs are significantly large, the best solution is to ship product everyday and hold no inventory.

货运支撑着美国的经济运行。公路货运是农业领域最常用的运输方式，而农业领域的多数供应商为小型农户，其运输需求普遍偏低。本研究聚焦于包含小型农户的供应链系统，针对易腐货物的运输问题共考量两种模型。两种模型均基于往返单一集货中心（consolidation center）的直运运输网络构建，我们将产品易腐性定义为其在集货中心停留总时长的硬约束条件。在第一种模型中，我们假设库存成本可忽略不计，仅考量运输成本。本研究提出一种高效且易于落地实施的集货启发式算法，该策略依托整车货运费率（full truckload rates）、零担货运费率（less-than-truckload rates）与快递货运费率（courier rates）三种运输方式的规模效应，同时构建动态规划（dynamic programming）模型以求解最优解，两种求解方法均可处理多供应商、季节性需求场景下直运集货模型的确定性与随机性案例。第二种模型在第一种模型的基础上，新增了库存成本与易腐性的软约束条件，本研究提出一种动态规划算法与一种启发式方法，用于权衡运输成本与库存持有成本。数值实验结果表明，当库存成本较高时，该启发式算法表现优异；但当库存成本极高时，最优策略为每日发货且不持有任何库存。