Computing optimal (R,s,S) policy parameters by a hybrid of branch-and-bound and stochastic dynamic programming

Visentin A., Prestwich S., Rossi R., TARIM Ş. A.

European Journal of Operational Research, cilt.294, sa.1, ss.91-99, 2021 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 294 Sayı: 1
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1016/j.ejor.2021.01.012
  • Dergi Adı: European Journal of Operational Research
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, International Bibliography of Social Sciences, ABI/INFORM, Applied Science & Technology Source, Business Source Elite, Business Source Premier, Computer & Applied Sciences, EconLit, INSPEC, Public Affairs Index, zbMATH, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.91-99
  • Anahtar Kelimeler: (R,s,S) policy, Demand uncertainty, Inventory, Stochastic lot sizing
  • Hacettepe Üniversitesi Adresli: Evet

Özet

A well-known control policy in stochastic inventory control is the (R,s,S) policy, in which inventory is raised to an order-up-to-level S at a review instant R whenever it falls below reorder-level s. To date, little or no work has been devoted to developing approaches for computing (R,s,S) policy parameters. In this work, we introduce a hybrid approach that exploits tree search to compute optimal replenishment cycles, and stochastic dynamic programming to compute (s,S) levels for a given cycle. Up to 99.8% of the search tree is pruned by a branch-and-bound technique with bounds generated by dynamic programming. A numerical study shows that the method can solve instances of realistic size in a reasonable time.