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

Dural-Selcuk G., Rossi R., Kilic O. A., TARIM Ş. A.

Omega (United Kingdom), cilt.97, 2020 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 97
  • Basım Tarihi: 2020
  • Doi Numarası: 10.1016/j.omega.2019.07.007
  • Dergi Adı: Omega (United Kingdom)
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus, ABI/INFORM, Business Source Elite, Business Source Premier, INSPEC, MLA - Modern Language Association Database, Violence & Abuse Abstracts
  • Anahtar Kelimeler: Dynamic uncertainty, Receding horizon control, Static uncertainty, Static-dynamic uncertainty, Stochastic lot sizing
  • Hacettepe Üniversitesi Adresli: Evet

Özet

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.