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A production inventory model for deteriorating item with ramp type demand allowing inflation and shortages under fuzziness

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  • Pal, Shilpi
  • Mahapatra, G.S.
  • Samanta, G.P.

Abstract

Economic production quantity (EPQ) is the quantity of a product that should be manufactured in a single batch so as to minimize the total cost. In classical model EPQ only applies where the demand for a product and production rate is constant over the year. But in reality these parameters vary with time in different scenarios. In this paper we have considered a production inventory model for deteriorating items with ramp type demand rate under the effect of inflation and shortages under fuzziness. The deterioration rate is represented by a two-parameter Weibull distribution. As inflation erodes the value of money so we have also considered the effect of inflation when there is shortage in the stock under finite time horizon. Some parameters are vaguely or unclearly defined or whose values are imprecise or determined based on subjective beliefs of individuals. Therefore the inventory model is solved under fuzzy environment to evaluate the optimum solution of the model in different cases. We have optimized our solution by considering production time and production rate as decision variables in two separate cases. While incorporating symmetric triangular fuzzy number we use total λ-integral value to defuzzify the solution. Finally, utility of the model is presented by using some numerical examples and sensitivity analysis and the results are analyzed.

Suggested Citation

  • Pal, Shilpi & Mahapatra, G.S. & Samanta, G.P., 2015. "A production inventory model for deteriorating item with ramp type demand allowing inflation and shortages under fuzziness," Economic Modelling, Elsevier, vol. 46(C), pages 334-345.
    • Handle: RePEc:eee:ecmode:v:46:y:2015:i:c:p:334-345
    DOI: 10.1016/j.econmod.2014.12.031
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    References listed on IDEAS

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    Cited by:

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    2. G. Durga Bhavani & Ieva Meidute-Kavaliauskiene & Ghanshaym S. Mahapatra & Renata Činčikaitė, 2022. "A Sustainable Green Inventory System with Novel Eco-Friendly Demand Incorporating Partial Backlogging under Fuzziness," Sustainability, MDPI, vol. 14(15), pages 1-20, July.
    3. M. Palanivel & R. Uthayakumar, 2016. "Two-warehouse inventory model for non-instantaneous deteriorating items with partial backlogging and inflation over a finite time horizon," OPSEARCH, Springer;Operational Research Society of India, vol. 53(2), pages 278-302, June.
    4. Santosh Shekhawat & Nazek Alessa & Himanshu Rathore & Kalpna Sharma, 2022. "A Green Approach—Cost Optimization for a Manufacturing Supply Chain with MFIFO Warehouse Dispatching Policy and Inspection Policy," Sustainability, MDPI, vol. 14(21), pages 1-17, November.
    5. Sudip Adak & G. S. Mahapatra, 2022. "Effect of reliability on multi-item inventory system with shortages and partial backlog incorporating time dependent demand and deterioration," Annals of Operations Research, Springer, vol. 315(2), pages 1551-1571, August.
    6. Pourmohammad Zia, Nadia & Taleizadeh, Ata Allah, 2015. "A lot-sizing model with backordering under hybrid linked-to-order multiple advance payments and delayed payment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 82(C), pages 19-37.
    7. Dai, Zhuo & Aqlan, Faisal & Gao, Kuo, 2017. "Optimizing multi-echelon inventory with three types of demand in supply chain," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 107(C), pages 141-177.
    8. Anushri Maji & Asoke Kumar Bhunia & Shyamal Kumar Mondal, 2022. "A production-reliability-inventory model for a series-parallel system with mixed strategy considering shortage, warranty period, credit period in crisp and stochastic sense," OPSEARCH, Springer;Operational Research Society of India, vol. 59(3), pages 862-907, September.
    9. Saha, Subrata & Sarkar, Biswajit & Sarkar, Mitali, 2023. "Application of improved meta-heuristic algorithms for green preservation technology management to optimize dynamical investments and replenishment strategies," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 209(C), pages 426-450.

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