On the Accuracy of Fluid Approximations to a Class of Inventory-Level-Dependent EOQ and EPQ Models

Author:

Piunovskiy Alexey1,Zhang Yi1

Affiliation:

1. Department of Mathematical Sciences, University of Liverpool, Liverpool, L69 7ZL, UK

Abstract

Deterministic Economic Order Quantity (EOQ) models have been studied intensively in the literature, where the demand process is described by an ordinary differential equation, and the objective is to obtain an EOQ, which minimizes the total cost per unit time. The total cost per unit time consists of a “discrete” part, the setup cost, which is incurred at the time of ordering, and a “continuous” part, the holding cost, which is continuously accumulated over time. Quite formally, such deterministic EOQ models can be viewed as fluid approximations to the corresponding stochastic EOQ models, where the demand process is taken as a stochastic jump process. Suppose now an EOQ is obtained from a deterministic model. The question is how well does this quantity work in the corresponding stochastic model. In the present paper we justify a translation of EOQs obtained from deterministic models, under which the resulting order quantities are asymptotically optimal for the stochastic models, by showing that the difference between the performance measures and the optimal values converges to zero with respect to a scaling parameter. Moreover, we provide an estimate for the rate of convergence. The same issue regarding specific Economic Production Quantity (EPQ) models is studied, too.

Publisher

Hindawi Limited

Subject

Management Science and Operations Research

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Economic Order Quantity Estimation with Uncertain External Information on Product Demand Quantile;Advances in Logistics, Operations, and Management Science;2023-07-10

2. Fluid Approximations to Markov Decision Processes with Local Transitions;Optimization, Control, and Applications of Stochastic Systems;2012

3. Accuracy of fluid approximations to controlled birth-and-death processes: absorbing case;Mathematical Methods of Operations Research;2010-12-23

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