基于不确定随机需求的周期性库存策略

摘要

In classic periodic inventory model,demand is usually considered as a random variable,but in production practice,the distribution function of new equipment demand cannot be obtained due to lack of historical sale data.So companies usually take product demand data of the original equipment as reference,and invite relevant experts to provide a subjective estimate to the unit demand distribution of new equipment.To describe the randomness and subjective uncertainty of the new equipment demand,chance theory is introduced and the demand is assumed as a uncertain random variable.A periodic order optimization model is built and an optimal analytical solution for profit maximization is obtained.Finally,numerical examples verify the feasibility of the current model,and a sensitivity analysis for parameters is taken.%经典的周期性库存模型中通常将需求视为随机变量,然而在生产实践中,当设备如民用飞机更新后由于缺乏历史运营数据,无法得到其零部件需求的分布函数.因此企业决策新设备零部件库存问题时通常会参考原设备的失效数据,并邀请相关领域专家给出新设备零部件需求的主观信度.为刻画新设备对该零件需求的随机性和主观不确定性,引入机会理论将需求假设为不确定随机变量,建立周期性订货优化模型,推导出使利润最大化时最优订货策略的解析解.最后,用数值算例验证该模型的可行性,并对各参数进行了敏感性分析.