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Preservation effort effects on retailers and manufacturers in integrated multi-deteriorating item discrete supply chain model

Author

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  • Monalisha Pattnaik

    (Sambalpur University)

  • Padmabati Gahan

    (Sambalpur University)

Abstract

This paper studies the multi-deteriorating item discrete supply chain to realize considerable savings by aggregating the replenishment. The present integrated replenishment policy has already been widely applied in a variety of industries. This study deals with an integrated multi-deteriorating item replenishment problem with preservation effort and discrete demand rate and discrete order quantity. Most existing studies about preservation effort focused on a single-item replenishment policy. However, integrated replenishment has been extensively applied in many industries to take advantage of economies of scale in preservation. Since it is difficult to solve this problem directly, the necessary and sufficient conditions with these properties are derived; a solution procedure and an algorithm using heuristic approach are developed to obtain the optimal solutions. Numerical examples, comparative analysis and sensitivity analyses are also provided and tested to elucidate the multi-deteriorating item discrete supply chain model with preservation efforts. The results reveal that the extensions of the model provide a wider and reasonable situation in practice, so that the annual channel profit can be maximized.

Suggested Citation

  • Monalisha Pattnaik & Padmabati Gahan, 2021. "Preservation effort effects on retailers and manufacturers in integrated multi-deteriorating item discrete supply chain model," OPSEARCH, Springer;Operational Research Society of India, vol. 58(2), pages 276-329, June.
    • Handle: RePEc:spr:opsear:v:58:y:2021:i:2:d:10.1007_s12597-020-00477-2
    DOI: 10.1007/s12597-020-00477-2
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    1. Lu, Lu, 1995. "A one-vendor multi-buyer integrated inventory model," European Journal of Operational Research, Elsevier, vol. 81(2), pages 312-323, March.
    2. Chen, Tsung-Hui & Chen, Jen-Ming, 2005. "Optimizing supply chain collaboration based on joint replenishment and channel coordination," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 41(4), pages 261-285, July.
    3. Tsao, Yu-Chung & Sheen, Gwo-Ji, 2012. "A multi-item supply chain with credit periods and weight freight cost discounts," International Journal of Production Economics, Elsevier, vol. 135(1), pages 106-115.
    4. Ateka Banu & Shyamal Kumar Mondal, 2018. "An integrated inventory model with warranty dependent credit period under two policies of a manufacturer," OPSEARCH, Springer;Operational Research Society of India, vol. 55(3), pages 677-702, November.
    5. Chen, Jen-Ming & Chen, Tsung-Hui, 2007. "The profit-maximization model for a multi-item distribution channel," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(4), pages 338-354, July.
    6. Edward P. C. Kao, 1979. "A Multi-Product Dynamic Lot-Size Model with Individual and Joint Set-up Costs," Operations Research, INFORMS, vol. 27(2), pages 279-289, April.
    7. T. V. S. R. K. Prasad & Kolla Srinivas & C. Srinivas, 2017. "Decentralized production–distribution planning in multi-echelon supply chain network using intelligent agents," OPSEARCH, Springer;Operational Research Society of India, vol. 54(2), pages 217-232, June.
    8. Wedad Elmaghraby & P{i}nar Keskinocak, 2003. "Dynamic Pricing in the Presence of Inventory Considerations: Research Overview, Current Practices, and Future Directions," Management Science, INFORMS, vol. 49(10), pages 1287-1309, October.
    9. S Viswanathan, 2002. "On optimal algorithms for the joint replenishment problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(11), pages 1286-1290, November.
    10. Abad, P. L. & Jaggi, C. K., 2003. "A joint approach for setting unit price and the length of the credit period for a seller when end demand is price sensitive," International Journal of Production Economics, Elsevier, vol. 83(2), pages 115-122, February.
    11. Juho Hahm & Candace Arai Yano, 1995. "The Economic Lot and Delivery Scheduling Problem: Powers of Two Policies," Transportation Science, INFORMS, vol. 29(3), pages 222-241, August.
    12. Viswanathan, S. & Piplani, Rajesh, 2001. "Coordinating supply chain inventories through common replenishment epochs," European Journal of Operational Research, Elsevier, vol. 129(2), pages 277-286, March.
    13. Khouja, Moutaz, 2003. "Optimizing inventory decisions in a multi-stage multi-customer supply chain," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 39(3), pages 193-208, May.
    14. Li, Xiuhui & Wang, Qinan, 2007. "Coordination mechanisms of supply chain systems," European Journal of Operational Research, Elsevier, vol. 179(1), pages 1-16, May.
    15. Bhattacharya, D. K., 2005. "On multi-item inventory," European Journal of Operational Research, Elsevier, vol. 162(3), pages 786-791, May.
    16. Dev Joneja, 1990. "The Joint Replenishment Problem: New Heuristics and Worst Case Performance Bounds," Operations Research, INFORMS, vol. 38(4), pages 711-723, August.
    17. Rempala, Ryszarda, 2003. "Joint replenishment multiproduct inventory problem with continuous production and discrete demands," International Journal of Production Economics, Elsevier, vol. 81(1), pages 495-511, January.
    18. Morris A. Cohen, 1977. "Joint pricing and ordering policy for exponentially decaying inventory with known demand," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 24(2), pages 257-268, June.
    19. Nejib Ben-Khedher & Candace A. Yano, 1994. "The Multi-Item Joint Replenishment Problem with Transportation and Container Effects," Transportation Science, INFORMS, vol. 28(1), pages 37-54, February.
    20. Miranda, Pablo A. & Garrido, Rodrigo A., 2004. "Incorporating inventory control decisions into a strategic distribution network design model with stochastic demand," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 40(3), pages 183-207, May.
    21. S. Viswanathan, 1997. "Note. Periodic Review (s, S) Policies for Joint Replenishment Inventory Systems," Management Science, INFORMS, vol. 43(10), pages 1447-1454, October.
    22. Stephen C. Graves, 1979. "Note--On the Deterministic Demand Multi-Product Single-Machine Lot Scheduling Problem," Management Science, INFORMS, vol. 25(3), pages 276-280, March.
    23. Hsu, P.H. & Wee, H.M. & Teng, H.M., 2010. "Preservation technology investment for deteriorating inventory," International Journal of Production Economics, Elsevier, vol. 124(2), pages 388-394, April.
    24. Terry A. Taylor, 2002. "Supply Chain Coordination Under Channel Rebates with Sales Effort Effects," Management Science, INFORMS, vol. 48(8), pages 992-1007, August.
    25. R Y K Fung & X Ma, 2001. "A new method for joint replenishment problems," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 52(3), pages 358-362, March.
    26. Lee, Wenyih, 2005. "A joint economic lot size model for raw material ordering, manufacturing setup, and finished goods delivering," Omega, Elsevier, vol. 33(2), pages 163-174, April.
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