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Multi-item imperfect production inventory model in Bi-fuzzy environments

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  • Ashoke Kumar Bera

    (Haldia Institue of Technology, Haldia)

  • Dipak Kumar Jana

    (Haldia Institute of Technology, Haldia)

Abstract

In this paper, we propose a mathematical model for a single period multi-product production inventory model producing stochastically imperfect items with continuous stochastic demand under budget and limited shortage constraints in Bi-fuzzy environment. The stochastic constraints are first converted into corresponding crisp values using expected value method. Here, we have considered the model as single period’s inventory for each item and the cycle lengths for different items are constant but different. Total demand for a cycle and the rate of production of defective units is considered as stochastic. The model is formulated and the expected average profits for each product are calculated from density function of demand and percentage of imperfectness in general form and then particular expressions are obtained by using appropriate boundary conditions. Here, all the constraints are Bi-fuzzy in nature and represented by possibility constraints. The deterministic problem is then solved by using generalized reduced gradient method. The model is illustrated through numerical examples. Sensitivity analysis on profit functions due to different aspiration and confidence level is presented via graphically.

Suggested Citation

  • Ashoke Kumar Bera & Dipak Kumar Jana, 2017. "Multi-item imperfect production inventory model in Bi-fuzzy environments," OPSEARCH, Springer;Operational Research Society of India, vol. 54(2), pages 260-282, June.
  • Handle: RePEc:spr:opsear:v:54:y:2017:i:2:d:10.1007_s12597-016-0283-4
    DOI: 10.1007/s12597-016-0283-4
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    References listed on IDEAS

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    2. Prasanta Kumar Ghosh & Amalesh Kumar Manna & Jayanta Kumar Dey & Samarjit Kar, 2023. "Optimal production run in an imperfect production process with maintenance under warranty and product insurance," OPSEARCH, Springer;Operational Research Society of India, vol. 60(2), pages 720-752, June.
    3. 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.
    4. Ashoke Kumar Bera & Dipak Kumar Jana & Debamalya Banerjee & Titas Nandy, 2021. "A Two-Phase Multi-criteria Fuzzy Group Decision Making Approach for Supplier Evaluation and Order Allocation Considering Multi-objective, Multi-product and Multi-period," Annals of Data Science, Springer, vol. 8(3), pages 577-601, September.

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