Abstract: Supplier’s supply capacity and economic benefits are not considered in the traditional material requirement planning, which is not conducive to long-term cooperation of enterprises in supply chain. Therefore, a synergy optimization problem of material purchasing is presented for JIT supply chain. Taking the secondary supply chain with a single manufacturer and multiple suppliers as the research object, following the BOM constraint and MRP principle, an optimizing model of material purchase is established to minimize the total cost of supply chain caused by inventory, transportation, stock out, crashing and so on. New delivery plans of suppliers can be obtained by adjusting the manufacturer’s master production schedule. An improved particle swarm optimization algorithm is designed and combined with genetic crossover and integer coding to solve the model. The model feasibility is demonstrated by a case study, and the validity of the algorithm is verified by result analyzing and comparing with the normal particle swarm algorithm and genetic algorithm.

Key words: Just In Time（JIT） supply chain, Material Require Planning（MRP）, synergy optimization, particle swarm algorithm

摘要： 在供应链环境中，传统的物料需求计划没有考虑供应商的供货能力与经济利益，不利于供应链上下游企业的长期合作。研究了一种基于JIT的供应链物料采购协同优化问题，以单一制造商和多供应商构成的二级供应链为研究对象，遵循产品生产的BOM约束和MRP制定原理，以最小化供应链上下游企业的库存、运输、缺货、赶工等总成本为目标，构建了以MRP为引导的供应链订购批量协同优化模型；通过调整制造商的主生产计划变更采购计划，以获得供应商供货方案，据此设计了基于整数编码和带有交叉操作的改进离散粒子群优化算法进行模型求解；结合实例对模型可行性进行了验证，通过算法结果分析及比较，证明了算法的有效性。

关键词: 准时生产（JIT）供应链, 物料需求计划（MRP）, 协同优化, 粒子群算法