Periodic review inventory models with multiclass demands and fixed order costs

IF 0.5 4区 数学 Q4 STATISTICS & PROBABILITY
V. Kulkarni, Li Xiao, Hanqin Zhang
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引用次数: 0

Abstract

Abstract We consider a periodic review inventory system with multiclass demands and fixed setup cost. Demand arrivals of each class are assumed to be a Poisson process, and a lost-sales setting is adopted. The demand classes are classified by the cost of their unsatisfied demands. We consider two cases: the leftover inventory at the end of a restocking interval is entirely discarded or entirely carried over to the next period. We obtain the optimal rationing policy, the optimal ordering policy and the optimal duration of the periodic review interval that minimize the average cost per unit time. We derive the differential equations satisfied by the value function characterized by the on-hand inventory level and the residual restocking time. This value function does not have the traditional modularity and convexity properties. Hence, the optimal policy is derived directly based on the ordinary differential equations satisfied by the value function. Moreover, some structural properties of the optimal policy such as the monotone property of the optimal rationing policy are obtained.
定期审查具有多类别需求和固定订单成本的库存模型
摘要考虑具有多类别需求和固定设置成本的定期复核库存系统。假设每个类别的需求到达是泊松过程,并采用损失销售设置。需求类别根据未满足需求的成本进行分类。我们考虑两种情况:在补充库存周期结束时剩余的库存被全部丢弃或全部结转到下一个期间。得到了使单位时间平均成本最小的最优配货策略、最优订货策略和最优评审间隔时间。导出了以库存水平和剩余补货时间为特征的价值函数所满足的微分方程。该值函数不具有传统的模块化和凸性。因此,直接根据值函数所满足的常微分方程推导出最优策略。此外,还得到了最优配给策略的单调性等最优策略的一些结构性质。
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来源期刊
Stochastic Models
Stochastic Models 数学-统计学与概率论
CiteScore
1.30
自引率
14.30%
发文量
42
审稿时长
>12 weeks
期刊介绍: Stochastic Models publishes papers discussing the theory and applications of probability as they arise in the modeling of phenomena in the natural sciences, social sciences and technology. It presents novel contributions to mathematical theory, using structural, analytical, algorithmic or experimental approaches. In an interdisciplinary context, it discusses practical applications of stochastic models to diverse areas such as biology, computer science, telecommunications modeling, inventories and dams, reliability, storage, queueing theory, mathematical finance and operations research.
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