The benefit of receding horizon control: Near-optimal policies for stochastic inventory control

Gozdem Dural-Selcuk, Roberto Rossi, Onur A. Kilic and S. Armagan Tarim

Omega, 2020, vol. 97, issue C

Abstract: In this paper we address the single-item, single-stocking point, non-stationary stochastic lot-sizing problem under backorder costs. It is well known that the (s, S) policy provides the optimal control for such inventory systems. However the computational difficulties and the nervousness inherent in (s, S) paved the way for the development of various near-optimal inventory control policies. We provide a systematic comparison of these policies and present their expected cost performances. We further show that when these policies are used in a receding horizon framework the cost performances improve considerably and differences among policies become insignificant.

Keywords: Stochastic lot sizing; Static uncertainty; Dynamic uncertainty; Static-dynamic uncertainty; Receding horizon control (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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DOI: 10.1016/j.omega.2019.07.007

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