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

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2020

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Pergamon-elsevier Science Ltd

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Industrial Engineering
(1998)
Industrial Engineering is a field of engineering that develops and applies methods and techniques to design, implement, develop and improve systems comprising of humans, materials, machines, energy and funding. Our department was founded in 1998, and since then, has graduated hundreds of individuals who may compete nationally and internationally into professional life. Accredited by MÜDEK in 2014, our student-centered education continues. In addition to acquiring the knowledge necessary for every Industrial engineer, our students are able to gain professional experience in their desired fields of expertise with a wide array of elective courses, such as E-commerce and ERP, Reliability, Tabulation, or Industrial Engineering Applications in the Energy Sector. With dissertation projects fictionalized on solving real problems at real companies, our students gain experience in the sector, and a wide network of contacts. Our education is supported with ERASMUS programs. With the scientific studies of our competent academic staff published in internationally-renowned magazines, our department ranks with the bests among other universities. IESC, one of the most active student networks at our university, continues to organize extensive, and productive events every year.

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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. (C) 2019 Elsevier Ltd. All rights reserved.

Description

Rossi, Roberto/0000-0001-7247-1010; Dural, Gozdem/0000-0002-9909-2720; Tarim, S. Armagan/0000-0001-5601-3968; Kilic, Onur/0000-0003-2136-8157

Keywords

Stochastic lot sizing, Static uncertainty, Dynamic uncertainty, Static-dynamic uncertainty, Receding horizon control

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7

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97

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https://doi.org/10.1016/j.omega.2019.07.007
 https://hdl.handle.net/20.500.14411/3200

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