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针对有装配线最小批量要求且供应商交货数量随机条件下的多物料订货量分配问题,以订货成本、采购成本、库存持有成本和拖期成本组成的总成本最小为优化目标,构建了混合整数随机规划模型;使用离散粒子群优化算法对模型进行求解,通过两组算例将粒子群优化算法与遗传算法和枚举算法进行了对比分析,算例结果验证了离散粒子群优化算法解决该问题的可行性和有效性。最后,通过一组实例分析了不同单位拖期成本和单位库存成本情形下的订货量分配方案以及单位拖期成本/单位库存成本这一比例对总成本的影响。实例结果表明,物料的订货量分配方案与单位拖期成本/单位库存成本有关,且总成本与该比例呈线性相关关系。
In order to solve the problem of multi-material quantity allocation under the condition of minimum quantity of assembly line and supplier’s delivery quantity under random condition, the least total cost of ordering cost, purchase cost, inventory holding cost and tardiness cost is the optimization objective, and a hybrid Integer stochastic programming model; the discrete particle swarm optimization algorithm is used to solve the model, the particle swarm optimization algorithm is compared with the genetic algorithm and the enumeration algorithm by two sets of examples. The results of the example verify that the discrete particle swarm optimization algorithm to solve the problem The feasibility and effectiveness of the problem. Finally, a set of examples is used to analyze the impact of the ratio of the order quantity allocation under different units’ trough cost and unit inventory cost, as well as the unit cost on the unit t / t cost / unit inventory cost. The results of the example show that the material quantity order plan is related to the unit toss cost / unit inventory cost, and the total cost is linearly related to the proportion.