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

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

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

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Files

OMEGA_2019_232_Revision 1_V0 (002).pdf(328.33 KB)

Accepted Version

Date

2019-07-24

Authors

Dural-Selcuk, Gozdem

Rossi, Roberto

Kilic, Onur A.

Tarim, S. Armagan

Publisher

Elsevier Ltd.

Published Version

10.1016/j.omega.2019.07.007

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

Citation

Dural-Selcuk, G., Rossi, R., Kilic, O. A. and Tarim, S. A. (2019) 'The benefit of receding horizon control: near-optimal policies for stochastic inventory control', Omega. doi: 10.1016/j.omega.2019.07.007