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A fuzzy integrated inventory system with end of life treatment: a possibility in sports industry

Author

Listed:
  • Ritu Motla

    (Swami Vivekanand Subharti University)

  • Ashok Kumar

    (Meerut College)

  • S. R. Singh

    (C. C. S. University)

  • Neha Saxena

    (Swami Vivekanand Subharti University)

Abstract

An integrated inventory system has different sources which are uncertain in nature thus rendering the system and its outcome with a high uncertainty. Thus, implementing fuzzy reasoning in inventory modelling is essential to manage uncertainties. This study has developed a model that deals with the production and replenishment co-ordination in a three-echelon supply chain involving two manufacturers and a retailer with fuzzy parameters formulated as triangular fuzzy numbers. The model is thus designed in a way that verifies the unreliable nature of the production process and segregates the defective products from the perfect products. The defective products are routed to another market where they can be sold at a reduced price while the perfect products reach the manufacturer and in turn, the retailer. In today’s scenario, it has become vital to incorporate green activities into supply chain management. Here the study provided an end of life treatment of the retired products and the reverse flow of products has been considered as the responsibility of the manufacturer. The model considers the costs of idle times at the end of both manufacturers. It is a general model that can be a useful equipment for any kind of product but to show its practicability, we have introduced the example of the tennis racket. It is demonstrated by the numerical examples that the collection of the buyback products is lucrative for the system and the vagueness in the demand parameter affects the most to the optimality instead of other parameters. Other managerial insights are also provided.

Suggested Citation

  • Ritu Motla & Ashok Kumar & S. R. Singh & Neha Saxena, 2021. "A fuzzy integrated inventory system with end of life treatment: a possibility in sports industry," OPSEARCH, Springer;Operational Research Society of India, vol. 58(4), pages 869-888, December.
    • Handle: RePEc:spr:opsear:v:58:y:2021:i:4:d:10.1007_s12597-020-00492-3
    DOI: 10.1007/s12597-020-00492-3
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    References listed on IDEAS

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    1. Salameh, M. K. & Jaber, M. Y., 2000. "Economic production quantity model for items with imperfect quality," International Journal of Production Economics, Elsevier, vol. 64(1-3), pages 59-64, March.
    2. S. K. Goyal, 1976. "Note--Note on "Manufacturing Cycle Time Determination for a Multi-Stage Economic Production Quantity Model"," Management Science, INFORMS, vol. 23(3), pages 332-333, November.
    3. Nughthoh Arfawi Kurdhi & Sri Maria Puji Lestari & Yuliana Susanti, 2015. "A fuzzy collaborative supply chain inventory model with controllable setup cost and service level constraint for imperfect items," International Journal of Applied Management Science, Inderscience Enterprises Ltd, vol. 7(2), pages 93-122.
    4. S.R. Singh & Chaman Singh, 2010. "Supply chain model with stochastic lead time under imprecise partially backlogging and fuzzy ramp-type demand for expiring items," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 8(4), pages 511-522.
    5. Dharmendra Yadav & S. R. Singh & Rachna Kumari, 2013. "Application Of Minimax Distribution Free Procedure And Chebyshev Approach In Mixed Inventory Model Involving Reducible Lead-Time And Setup Cost With Imprecise Demand," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 30(04), pages 1-25.
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    Cited by:

    1. Saxena, Neha & Sarkar, Biswajit, 2023. "How does the retailing industry decide the best replenishment strategy by utilizing technological support through blockchain?," Journal of Retailing and Consumer Services, Elsevier, vol. 71(C).

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