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

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