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Pricing, inventory and production policies in a supply chain of pharmacological products with rework process: a game theoretic approach

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  • Ata Allah Taleizadeh

    (University of Tehran)

  • Mahsa Noori-daryan

    (University of Tehran)

Abstract

In this paper, an economic production quantity model in a three levels supply chain including multiple non-competing suppliers, single manufacturer and multiple non-competing retailers for multiple products with rework process under integrated and non-integrated structures is developed. In this chain, suppliers ship raw material to the manufacturer and the manufacturer combines the fixed percentage of different kinds of raw material to produce the finished products and then delivers them to the retailers. The Stackelberg game is established among the members of the chain. Optimizing the total profit of the chain under both structures applying the optimal pricing, inventory and production policies is the purpose of the research. Eventually, a numerical example is presented for comparing the total profit of the integrated and non-integrated chains of proposed model and some sensitivity analyses are performed to study the effects of parameter changes on the decision variables and the chain profit.

Suggested Citation

  • Ata Allah Taleizadeh & Mahsa Noori-daryan, 2016. "Pricing, inventory and production policies in a supply chain of pharmacological products with rework process: a game theoretic approach," Operational Research, Springer, vol. 16(1), pages 89-115, April.
    • Handle: RePEc:spr:operea:v:16:y:2016:i:1:d:10.1007_s12351-015-0188-7
    DOI: 10.1007/s12351-015-0188-7
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    References listed on IDEAS

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    Cited by:

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    2. Mohammad Reza Gholamian & Mahdi Ebrahimzadeh-Afruzi, 2021. "Credit and discount incentive options for two-level supply chain coordination, under uncertain price-dependent demand," Operational Research, Springer, vol. 21(4), pages 2283-2307, December.
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    4. Tang, Xiaoying & He, Yong & Salling, Melissza, 2021. "Optimal pricing and production strategies for two manufacturers with industrial symbiosis," International Journal of Production Economics, Elsevier, vol. 235(C).
    5. Noori-Daryan, Mahsa & Taleizadeh, Ata Allah & Jolai, Fariborz, 2019. "Analyzing pricing, promised delivery lead time, supplier-selection, and ordering decisions of a multi-national supply chain under uncertain environment," International Journal of Production Economics, Elsevier, vol. 209(C), pages 236-248.
    6. Ata Allah Taleizadeh & Masoumeh Sadat Babaei & Seyed Taghi Akhavan Niaki & Mahsa Noori-daryan, 2020. "Bundle pricing and inventory decisions on complementary products," Operational Research, Springer, vol. 20(2), pages 517-541, June.
    7. Madjid Tavana & Hannan Amoozad Mahdiraji & Moein Beheshti & Ali‐Asghar Abbasi Kamardi, 2020. "Optimal strategic alliance in multi‐echelon supply chains with open innovation," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 41(7), pages 1365-1384, October.
    8. Soheyl Khalilpourazari & Seyed Hamid Reza Pasandideh, 2020. "Multi-objective optimization of multi-item EOQ model with partial backordering and defective batches and stochastic constraints using MOWCA and MOGWO," Operational Research, Springer, vol. 20(3), pages 1729-1761, September.
    9. Ali Salmasnia & Ali Talesh-Kazemi, 2022. "Integrating inventory planning, pricing and maintenance for perishable products in a two-component parallel manufacturing system with common cause failures," Operational Research, Springer, vol. 22(2), pages 1235-1265, April.
    10. Jauhari, Wakhid Ahmad & Adam, Niimas Ayu Frensilia Putri & Rosyidi, Cucuk Nur & Pujawan, I Nyoman & Shah, Nita H., 2020. "A closed-loop supply chain model with rework, waste disposal, and carbon emissions," Operations Research Perspectives, Elsevier, vol. 7(C).
    11. Ata Allah Taleizadeh & Milad Shahriari & Shib Sankar Sana, 2021. "Pricing and Coordination Strategies in a Dual Channel Supply Chain with Green Production under Cap and Trade Regulation," Sustainability, MDPI, vol. 13(21), pages 1-18, November.

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