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Optimal policies for inventory systems with finite capacity and partially observed Markov-modulated demand and supply processes

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  • Arifoglu, Kenan
  • Özekici, Süleyman

Abstract

We analyze a single-item periodic-review inventory system with random yield and finite capacity operating in a random environment. The primary objective is to extend the model of Gallego and Hu (2004) to the more general case when the environment is only partially observable. Although our analysis is specific to inventory systems, it can also be applied to production systems by replacing the fixed capacity supplier with a fixed capacity producer. Using sufficient statistics, we consider single-period, multiple-period and infinite-period problems to show that a state-dependent modified inflated base-stock policy is optimal. Moreover, we show that the multiple-period cost converges to the infinite-period cost as the length of the planning horizon increases.

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  • Arifoglu, Kenan & Özekici, Süleyman, 2010. "Optimal policies for inventory systems with finite capacity and partially observed Markov-modulated demand and supply processes," European Journal of Operational Research, Elsevier, vol. 204(3), pages 421-438, August.
    • Handle: RePEc:eee:ejores:v:204:y:2010:i:3:p:421-438
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    2. Arifoglu, Kenan & Özekici, Süleyman, 2011. "Inventory management with random supply and imperfect information: A hidden Markov model," International Journal of Production Economics, Elsevier, vol. 134(1), pages 123-137, November.
    3. Kutzner, Sarah C. & Kiesmüller, Gudrun P., 2013. "Optimal control of an inventory-production system with state-dependent random yield," European Journal of Operational Research, Elsevier, vol. 227(3), pages 444-452.
    4. Kimitoshi Sato & Kyoko Yagi & Masahito Shimazaki, 2018. "A Stochastic Inventory Model for a Random Yield Supply Chain with Wholesale-Price and Shortage Penalty Contracts," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 35(06), pages 1-30, December.
    5. Pirayesh Neghab, Davood & Khayyati, Siamak & Karaesmen, Fikri, 2022. "An integrated data-driven method using deep learning for a newsvendor problem with unobservable features," European Journal of Operational Research, Elsevier, vol. 302(2), pages 482-496.
    6. Komeyl Baghizadeh & Nafiseh Ebadi & Dominik Zimon & Luay Jum’a, 2022. "Using Four Metaheuristic Algorithms to Reduce Supplier Disruption Risk in a Mathematical Inventory Model for Supplying Spare Parts," Mathematics, MDPI, vol. 11(1), pages 1-19, December.
    7. Bendre, Abhijit Bhagwan & Nielsen, Lars Relund, 2013. "Inventory control in a lost-sales setting with information about supply lead times," International Journal of Production Economics, Elsevier, vol. 142(2), pages 324-331.
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    10. Sayın, F. & Karaesmen, F. & Özekici, S., 2014. "Newsvendor model with random supply and financial hedging: Utility-based approach," International Journal of Production Economics, Elsevier, vol. 154(C), pages 178-189.
    11. Hekimoğlu, Mustafa & van der Laan, Ervin & Dekker, Rommert, 2018. "Markov-modulated analysis of a spare parts system with random lead times and disruption risks," European Journal of Operational Research, Elsevier, vol. 269(3), pages 909-922.
    12. Chen, Junlin & Zhao, Xiaobo & Zhou, Yun, 2012. "A periodic-review inventory system with a capacitated backup supplier for mitigating supply disruptions," European Journal of Operational Research, Elsevier, vol. 219(2), pages 312-323.
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    14. Landon, Joshua & Özekici, Süleyman & Soyer, Refik, 2013. "A Markov modulated Poisson model for software reliability," European Journal of Operational Research, Elsevier, vol. 229(2), pages 404-410.

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