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Non-instantaneous deterioration effect in ordering decisions for a two-warehouse inventory system under advance payment and backlogging

Author

Listed:
  • Md. Al-Amin Khan

    (Jahangirnagar University)

  • Ali Akbar Shaikh

    (University of Burdwan)

  • Gobinda Chandra Panda

    (Mahavir Institute of Engineering and Technology, BBSR)

  • Asoke Kumar Bhunia

    (University of Burdwan)

  • Ioannis Konstantaras

    (University of Macedonia)

Abstract

The process of deterioration may not start immediately after the consignment reaches the go down; there generally occurs a delay. In certain cases, deterioration might begin after a certain period which may further prolong due to the introduction of better methods of inventory management. To take into cognizance of these situations, in contrast to the ordinary assumption in the existing models, we have considered that the decay in owned warehouse begins earlier than that in case of rented warehouse as the latter always provides for better inventory management and facilities. Applying these phenomena, a two-storage inventory model has been formulated with advance payment under three different situations according to different possibilities of starting times of deterioration in both warehouses. In this model, demand depends upon the selling price wherein shortages are considered partially with fixed backlogging rate. Analyzing and investigating the proposed problem, three different optimization problems are formulated and the optimality of these problems is proved theoretically. To solve the model, an algorithm is proposed. Then, to illustrate the model numerically, an example is considered and solved. Finally, post optimality is performed in order to investigate the effects of changes of different system parameters.

Suggested Citation

  • Md. Al-Amin Khan & Ali Akbar Shaikh & Gobinda Chandra Panda & Asoke Kumar Bhunia & Ioannis Konstantaras, 2020. "Non-instantaneous deterioration effect in ordering decisions for a two-warehouse inventory system under advance payment and backlogging," Annals of Operations Research, Springer, vol. 289(2), pages 243-275, June.
  • Handle: RePEc:spr:annopr:v:289:y:2020:i:2:d:10.1007_s10479-020-03568-x
    DOI: 10.1007/s10479-020-03568-x
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    References listed on IDEAS

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    Cited by:

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    2. Mamta Gupta & Sunil Tiwari & Chandra K. Jaggi, 2020. "Retailer’s ordering policies for time-varying deteriorating items with partial backlogging and permissible delay in payments in a two-warehouse environment," Annals of Operations Research, Springer, vol. 295(1), pages 139-161, December.
    3. Khan, Md. Al-Amin & Shaikh, Ali Akbar & Cárdenas-Barrón, Leopoldo Eduardo, 2021. "An inventory model under linked-to-order hybrid partial advance payment, partial credit policy, all-units discount and partial backlogging with capacity constraint," Omega, Elsevier, vol. 103(C).
    4. Ranveer Singh Rana & Dinesh Kumar & Kanika Prasad & K. Mathiyazhagan, 2024. "Mitigating the impact of demand disruption on perishable inventory in a two-warehouse system," Operations Management Research, Springer, vol. 17(2), pages 469-504, June.
    5. Mahmood Vahdani & Zeinab Sazvar & Kannan Govindan, 2022. "An integrated economic disposal and lot-sizing problem for perishable inventories with batch production and corrupt stock-dependent holding cost," Annals of Operations Research, Springer, vol. 315(2), pages 2135-2167, August.
    6. Praveendra Singh & Madhu Jain, 2024. "Inventory policy for degrading items under advanced payment with price and memory sensitive demand using metaheuristic techniques," Operational Research, Springer, vol. 24(3), pages 1-34, September.
    7. Biman Kanti Nath & Nabendu Sen, 2022. "A Partially Backlogged Inventory Model for Time-Deteriorating Items Using Penalty Cost and Time-Dependent Holding Cost," SN Operations Research Forum, Springer, vol. 3(4), pages 1-14, December.
    8. Md. Abdul Hakim & Ibrahim M. Hezam & Adel Fahad Alrasheedi & Jeonghwan Gwak, 2022. "Pricing Policy in an Inventory Model with Green Level Dependent Demand for a Deteriorating Item," Sustainability, MDPI, vol. 14(8), pages 1-16, April.

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