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

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

*Corresponding author for this work

    Research output: Contribution to journalArticleAcademicpeer-review

    12 Citations (Scopus)
    232 Downloads (Pure)

    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.

    Original languageEnglish
    Article number102091
    Number of pages9
    JournalOmega: The International Journal of Management Science
    Volume97
    DOIs
    Publication statusPublished - Dec-2020

    Keywords

    • Stochastic lot sizing
    • Static uncertainty
    • Dynamic uncertainty
    • Static-dynamic uncertainty
    • Receding horizon control
    • LOT-SIZING PROBLEM
    • SYSTEMS
    • DEMAND
    • UNCERTAINTY
    • INSTABILITY
    • CONSTRAINT
    • COST

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