具有随机缺陷率产品的多点转运库存优化模型

Multi-location inventory optimization model with lateral transshipment for random defect rate items

为了研究具有随机缺陷率产品的多点库存管理问题,以零售商自有库存满足市场需求的比率为服务水平约束,构建了由一个制造商和多个零售商组成的供应链系统的库存优化模型,在允许零售商之间进行横向转运的情形下,以最大订购点S和库存转运控制点H作为决策变量,实现系统总成本最小;根据问题和模型的特点,采用改进自适应遗传算法对模型进行求解。通过数值研究结果验证了模型在成本优化方面的显著性和自适应遗传算法的有效性,并分析了服务水平约束和随机缺陷率等参数对库存成本和订购数量的影响,以求为多点转运库存优化问题提供一定的理论和实践指导。

To study the multiple demand spots inventory strategy with random defective rate products,a supply chain system composed of a manufacturer and multiple retailers was considered.Lateral transshipment between retailers was allowed in this system.Proportion of total demand satisfied by the retailer s own inventory was taken as a service level constraint.The maximum order point S and the inventory control point H as decision variables were used to minimize the total system cost.An improved adaptive genetic algorithm was designed according to the problem characteristics and was used to solve it.Numerical examples showed the significance of the model in cost optimization and the effectiveness of the algorithm,and analyzed the impact of service level and random defect rate’s changes on the total cost and order.It was also provided a theoretical and practical guidance for the optimization problem of multiple demand spots inventory with lateral transshipment.