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Optimizing EOQ Model for Carbon Emission Under Inflation for Expiring Items

In: Applications of Operational Research in Business and Industries

Author

Listed:
  • Chaman Singh

    (Acharya Narendra Dev College, University of Delhi)

  • Gurudatt Rao Ambedkar

    (University of Delhi)

Abstract

Nowadays, ventures like the supermarket industry are confronting numerous difficulties to meet the objectives of sustainable development. The client’s choices are changing at a quicker speed because of new advances and quickly changing the general climate. It is seen that demand of the items is straightforwardly associated with the stock level however keeping a colossal stock reason for increment in holding cost and crumbling effect. It is a major test to sell the whole lot before its lapse with the goal that its impact on climate can be diminished. In the changing environment, storage and managing of inventory items in the supermarket also play a major contribution in green house gas emission; consequently, supermarkets are enforced to make efforts to reduce the emission which also affects the behaviour of an inventory. Deterioration and inflation also have a significant effect on any model, thus cannot be ignored. This study optimizes and EOQ model for expiring items with stock, selling cost and lifetime-dependent demand which gives an ideal yield to acquire the most extreme benefit under inflationary conditions with carbon emission. The model is tackled mathematically to validate the analytical results, which would expand the all-out benefit. Sensitivity analysis strengthens the applicability of the model.

Suggested Citation

  • Chaman Singh & Gurudatt Rao Ambedkar, 2023. "Optimizing EOQ Model for Carbon Emission Under Inflation for Expiring Items," Lecture Notes in Operations Research, in: Angappa Gunasekaran & Jai Kishore Sharma & Samarjit Kar (ed.), Applications of Operational Research in Business and Industries, chapter 0, pages 395-411, Springer.
  • Handle: RePEc:spr:lnopch:978-981-19-8012-1_26
    DOI: 10.1007/978-981-19-8012-1_26
    as

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