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An inventory model under price and stock dependent demand for controllable deterioration rate with shortages and preservation technology investment

Author

Listed:
  • Umakanta Mishra

    (ICFAI University, Tripura)

  • Leopoldo Eduardo Cárdenas-Barrón

    (Tecnológico de Monterrey)

  • Sunil Tiwari

    (University of Delhi)

  • Ali Akbar Shaikh

    (Tecnológico de Monterrey)

  • Gerardo Treviño-Garza

    (BNSF Railway Company)

Abstract

This paper develops an EOQ inventory model that considers the demand rate as a function of stock and selling price. Shortages are permitted and two cases are studied: (i) complete backordering and (ii) partial backordering. The inventory model is for a deteriorating seasonal product. The product’s deterioration rate is controlled by investing in the preservation technology. The main purpose of the inventory model is to determine the optimum selling price, ordering frequency and preservation technology investment that maximizes the total profit. Additionally, the paper proves that the total profit is a concave function of selling price, ordering frequency and preservation technology investment. Therefore, a simple algorithm is proposed to obtain the optimal values for the decision variables. Several numerical examples are solved and studied along with a sensitivity analysis.

Suggested Citation

  • Umakanta Mishra & Leopoldo Eduardo Cárdenas-Barrón & Sunil Tiwari & Ali Akbar Shaikh & Gerardo Treviño-Garza, 2017. "An inventory model under price and stock dependent demand for controllable deterioration rate with shortages and preservation technology investment," Annals of Operations Research, Springer, vol. 254(1), pages 165-190, July.
  • Handle: RePEc:spr:annopr:v:254:y:2017:i:1:d:10.1007_s10479-017-2419-1
    DOI: 10.1007/s10479-017-2419-1
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    References listed on IDEAS

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    1. K. Skouri & I. Konstantaras & S. Manna & K. Chaudhuri, 2011. "Inventory models with ramp type demand rate, time dependent deterioration rate, unit production cost and shortages," Annals of Operations Research, Springer, vol. 191(1), pages 73-95, November.
    2. Dye, Chung-Yuan & Hsieh, Tsu-Pang, 2012. "An optimal replenishment policy for deteriorating items with effective investment in preservation technology," European Journal of Operational Research, Elsevier, vol. 218(1), pages 106-112.
    3. Lihao Lu & Jianxiong Zhang & Wansheng Tang, 2016. "Optimal dynamic pricing and replenishment policy for perishable items with inventory-level-dependent demand," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(6), pages 1480-1494, April.
    4. Chih-Te Yang, 2010. "The optimal order and payment policies for deteriorating items in discount cash flows analysis under the alternatives of conditionally permissible delay in payments and cash discount," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 18(2), pages 429-443, December.
    5. Burwell, Timothy H. & Dave, Dinesh S. & Fitzpatrick, Kathy E. & Roy, Melvin R., 1997. "Economic lot size model for price-dependent demand under quantity and freight discounts," International Journal of Production Economics, Elsevier, vol. 48(2), pages 141-155, January.
    6. P-S You, 2005. "Inventory policy for products with price and time-dependent demands," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(7), pages 870-873, July.
    7. Chakrabarti, T. & Chaudhuri, K. S., 1997. "An EOQ model for deteriorating items with a linear trend in demand and shortages in all cycles," International Journal of Production Economics, Elsevier, vol. 49(3), pages 205-213, May.
    8. Guowei Liu & Jianxiong Zhang & Wansheng Tang, 2015. "Joint dynamic pricing and investment strategy for perishable foods with price-quality dependent demand," Annals of Operations Research, Springer, vol. 226(1), pages 397-416, March.
    9. 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.
    10. Hou, Kuo-Lung, 2006. "An inventory model for deteriorating items with stock-dependent consumption rate and shortages under inflation and time discounting," European Journal of Operational Research, Elsevier, vol. 168(2), pages 463-474, January.
    11. Chandra K. Jaggi & Sunil Tiwari & Satish K. Goel, 2017. "Credit financing in economic ordering policies for non-instantaneous deteriorating items with price dependent demand and two storage facilities," Annals of Operations Research, Springer, vol. 248(1), pages 253-280, January.
    12. Nita Shah, 2015. "Retailer’s replenishment and credit policies for deteriorating inventory under credit period-dependent demand and bad-debt loss," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(1), pages 298-312, April.
    13. Hariga, Moncer A. & Benkherouf, Lakdere, 1994. "Optimal and heuristic inventory replenishment models for deteriorating items with exponential time-varying demand," European Journal of Operational Research, Elsevier, vol. 79(1), pages 123-137, November.
    14. Goyal, S. K. & Giri, B. C., 2001. "Recent trends in modeling of deteriorating inventory," European Journal of Operational Research, Elsevier, vol. 134(1), pages 1-16, October.
    15. Dye, Chung-Yuan, 2013. "The effect of preservation technology investment on a non-instantaneous deteriorating inventory model," Omega, Elsevier, vol. 41(5), pages 872-880.
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