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Flexible service policies for a Markov inventory system with two demand classes

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  • Liu, Mingwu
  • Feng, Mengying
  • Wong, Chee Yew

Abstract

This paper explores flexible service policies for an (r, Q) Markov inventory system with two classes of customers, ordinary and prioritized customers. When the on-hand inventory drops to pre-determined safety level r, arrival ordinary customers receive service at probability p. Firstly, the inventory level state transitions equation is set up. The steady-state probability distribution and the system's performance measures which are used for the inventory control are derived. Next, a long-run average inventory cost function is established and a mixed integer optimization model is set up. And, an improved genetic algorithm for the optimum control policies is presented. Finally, the optimal inventory control polices and the sensitivities are investigated through numerical experiments.

Suggested Citation

  • Liu, Mingwu & Feng, Mengying & Wong, Chee Yew, 2014. "Flexible service policies for a Markov inventory system with two demand classes," International Journal of Production Economics, Elsevier, vol. 151(C), pages 180-185.
    • Handle: RePEc:eee:proeco:v:151:y:2014:i:c:p:180-185
    DOI: 10.1016/j.ijpe.2013.10.010
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    References listed on IDEAS

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    Cited by:

    1. Shih-Hsien Tseng & Jia-Chen Yu, 2019. "Data-Driven Iron and Steel Inventory Control Policies," Mathematics, MDPI, vol. 7(8), pages 1-15, August.
    2. Thulaseedharan Salini Sinu Lal & Varghese Chaukayil Joshua & Vladimir Vishnevsky & Dmitry Kozyrev & Achyutha Krishnamoorthy, 2022. "A Multi-Type Queueing Inventory System—A Model for Selection and Allocation of Spectra," Mathematics, MDPI, vol. 10(5), pages 1-11, February.
    3. Stratos Ioannidis & Alexandros S. Xanthopoulos & Ioannis Sarantis & Dimitrios E. Koulouriotis, 2021. "Joint production, inventory rationing, and order admission control of a stochastic manufacturing system with setups," Operational Research, Springer, vol. 21(2), pages 827-855, June.
    4. Manafzadeh Dizbin, Nima & Tan, Barış, 2020. "Optimal control of production-inventory systems with correlated demand inter-arrival and processing times," International Journal of Production Economics, Elsevier, vol. 228(C).
    5. Umay Uzunoglu Kocer & Bahar Yalcin, 2020. "Continuous review (s, Q) inventory system with random lifetime and two demand classes," OPSEARCH, Springer;Operational Research Society of India, vol. 57(1), pages 104-118, March.
    6. Fathi, Mahdi & Khakifirooz, Marzieh & Diabat, Ali & Chen, Huangen, 2021. "An integrated queuing-stochastic optimization hybrid Genetic Algorithm for a location-inventory supply chain network," International Journal of Production Economics, Elsevier, vol. 237(C).
    7. Mohammad Najjartabar Bisheh & G. Reza Nasiri & Esmaeil Esmaeili & Hamid Davoudpour & Shing I. Chang, 2022. "A new supply chain distribution network design for two classes of customers using transfer recurrent neural network," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(5), pages 2604-2618, October.
    8. Serife Ozkar & Umay Uzunoglu Kocer, 2021. "Two-commodity queueing-inventory system with two classes of customers," OPSEARCH, Springer;Operational Research Society of India, vol. 58(1), pages 234-256, March.

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