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An Imperfect Production Model for Breakable Multi-Item with Dynamic Demand and Learning Effect on Rework over Random Planning Horizon

Author

Listed:
  • Amalesh Kumar Manna

    (Department of Mathematics, The University of Burdwan, Burdwan 713104, India)

  • Leopoldo Eduardo Cárdenas-Barrón

    (Tecnologico de Monterrey, School of Engineering and Sciences, Ave. Eugenio Garza Sada 2501, Monterrey 64849, Mexico)

  • Barun Das

    (Department of Mathematics, Sidho-Kanho-Birsha University, Purulia 723104, India)

  • Ali Akbar Shaikh

    (Department of Mathematics, The University of Burdwan, Burdwan 713104, India)

  • Armando Céspedes-Mota

    (Tecnologico de Monterrey, School of Engineering and Sciences, Ave. Eugenio Garza Sada 2501, Monterrey 64849, Mexico)

  • Gerardo Treviño-Garza

    (Tecnologico de Monterrey, School of Engineering and Sciences, Ave. Eugenio Garza Sada 2501, Monterrey 64849, Mexico)

Abstract

In recent times, in the literature of inventory management there exists a notorious interest in production-inventory models focused on imperfect production processes with a deterministic time horizon. Nevertheless, it is well-known that there is a high influence and impact caused by the learning effect on the production-inventory models in the random planning horizon. This research work formulates a mathematical model for a re-workable multi-item production-inventory system, in which the demand of the items depends on the accessible stock and selling revenue. The production-inventory model allows shortages and these are partial backlogged over a random planning horizon. Also, the learning effect on the rework policy, inflation, and the time value of money are considered. The main aim is to determine the optimum production rates that minimize the expected total cost of the multi-item production-inventory system. A numerical example is solved and a detailed sensitivity analysis is conducted in order to study the production-inventory model.

Suggested Citation

  • Amalesh Kumar Manna & Leopoldo Eduardo Cárdenas-Barrón & Barun Das & Ali Akbar Shaikh & Armando Céspedes-Mota & Gerardo Treviño-Garza, 2021. "An Imperfect Production Model for Breakable Multi-Item with Dynamic Demand and Learning Effect on Rework over Random Planning Horizon," JRFM, MDPI, vol. 14(12), pages 1-20, November.
  • Handle: RePEc:gam:jjrfmx:v:14:y:2021:i:12:p:574-:d:691260
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    References listed on IDEAS

    as
    1. Padmanabhan, G. & Vrat, Prem, 1995. "EOQ models for perishable items under stock dependent selling rate," European Journal of Operational Research, Elsevier, vol. 86(2), pages 281-292, October.
    2. Cardenas-Barron, Leopoldo Eduardo, 2001. "The economic production quantity (EPQ) with shortage derived algebraically," International Journal of Production Economics, Elsevier, vol. 70(3), pages 289-292, April.
    3. Pal, S. & Goswami, A. & Chaudhuri, K. S., 1993. "A deterministic inventory model for deteriorating items with stock-dependent demand rate," International Journal of Production Economics, Elsevier, vol. 32(3), pages 291-299, November.
    4. P. L. Abad, 1996. "Optimal Pricing and Lot-Sizing Under Conditions of Perishability and Partial Backordering," Management Science, INFORMS, vol. 42(8), pages 1093-1104, August.
    Full references (including those not matched with items on IDEAS)

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