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http://hdl.handle.net/10397/98611
Title: | Ergodic control for a mean reverting inventory model | Authors: | Liu, J Yiu, KFC Bensoussan, A |
Issue Date: | Jul-2018 | Source: | Journal of industrial and management optimization, July 2018, v. 14, no. 3, p. 857-876 | Abstract: | In this paper, an inventory control problem with a mean reverting inventory model is considered. The demand is assumed to follow a continuous diffusion process and a mean-reverting process which will take into account of the demand dependent of the inventory level. By choosing when and how much to stock, the objective is to minimize the long-run average cost, which consists of transaction cost for each replenishment, holding and shortage costs associated with the inventory level. An approach for deriving the average cost value of infinite time horizon is developed. By applying the theory of stochastic impulse control, we show that a unique (s, S) policy is indeed optimal. The main contribution of this work is to present a method to derive the (s, S) policy and hence the minimal long-run average cost. | Keywords: | Dynamic programming Inventory policy Mean reverting model Ergodic control Stochastic impulse control |
Publisher: | AIMS Press | Journal: | Journal of industrial and management optimization | ISSN: | 1547-5816 | EISSN: | 1553-166X | DOI: | 10.3934/jimo.2017079 | Rights: | © American Institute of Mathematical Sciences This article has been published in a revised form in Journal of Industrial and Management Optimization http://dx.doi.org/10.3934/jimo.2017079. This version is free to download for private research and study only. Not for redistribution, re-sale or use in derivative works. |
Appears in Collections: | Journal/Magazine Article |
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Yiu_Ergodic_Control_Mean.pdf | Pre-Published version | 879.41 kB | Adobe PDF | View/Open |
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