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Economic growing quantity

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  • Gharaei, Abolfazl
  • Almehdawe, Eman

Abstract

The essence of some items is continuously growing and gaining weight over time. These are known as growing items, which their weights and values increase over time. This paper provides a new generation of inventory models, entitled Economic Growing Quantity (EGQ), which is designed by focusing on growing items of agricultural industries such as fisheries, poultry, and livestock. Our EGQ inventory model considers the probability density functions of survival and mortality for a growing item. It also considers the growth functions of live and dead grown items. Accordingly, the total cost for EGQ model consists of the costs of purchasing process, the disposal cost of dead items, the holding cost, the feeding cost, and the setup costs for both the live and the dead items. Our goal is to determine the optimal economic growth/slaughter cycle and the economic growing quantity in order to minimize the total costs. Subsequently, we optimize the weight of slaughtering, the Utility of Growth Functions (UGF), and other important performance metrics of the system. The applicability and validity of our model is demonstrated based on numerical examples of the poultry industry. The results of sensitivity analyses recommend some strategic implications and insights for the managers of growing items.

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  • Gharaei, Abolfazl & Almehdawe, Eman, 2020. "Economic growing quantity," International Journal of Production Economics, Elsevier, vol. 223(C).
    • Handle: RePEc:eee:proeco:v:223:y:2020:i:c:s092552731930338x
    DOI: 10.1016/j.ijpe.2019.107517
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    1. Guchhait, Partha & Kumar Maiti, Manas & Maiti, Manoranjan, 2013. "Production-inventory models for a damageable item with variable demands and inventory costs in an imperfect production process," International Journal of Production Economics, Elsevier, vol. 144(1), pages 180-188.
    2. Glock, C. H., 2012. "Lead time reduction strategies in a single-vendor-single-buyer integrated inventory model with lot size-dependent lead times and stochastic demand," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 57816, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    3. Matsuyama, Keisuke, 2001. "The EOQ-Models modified by introducing discount of purchase price or increase of setup cost," International Journal of Production Economics, Elsevier, vol. 73(1), pages 83-99, August.
    4. Goyal, S. K. & Giri, B. C., 2001. "Recent trends in modeling of deteriorating inventory," European Journal of Operational Research, Elsevier, vol. 134(1), pages 1-16, October.
    5. Gour Chandra Mahata & Sujit Kumar De, 2016. "An EOQ inventory system of ameliorating items for price dependent demand rate under retailer partial trade credit policy," OPSEARCH, Springer;Operational Research Society of India, vol. 53(4), pages 889-916, December.
    6. Fangruo Chen, 1998. "Echelon Reorder Points, Installation Reorder Points, and the Value of Centralized Demand Information," Management Science, INFORMS, vol. 44(12-Part-2), pages 221-234, December.
    7. Matsuyama, Keisuke, 1995. "Inventory policy with time-dependent setup cost," International Journal of Production Economics, Elsevier, vol. 42(2), pages 149-160, December.
    8. Rezaei, Jafar, 2014. "Economic order quantity for growing items," International Journal of Production Economics, Elsevier, vol. 155(C), pages 109-113.
    9. Glock, Christoph H., 2012. "Lead time reduction strategies in a single-vendor–single-buyer integrated inventory model with lot size-dependent lead times and stochastic demand," International Journal of Production Economics, Elsevier, vol. 136(1), pages 37-44.
    10. Noblesse, Ann M. & Boute, Robert N. & Lambrecht, Marc R. & Van Houdt, Benny, 2014. "Lot sizing and lead time decisions in production/inventory systems," International Journal of Production Economics, Elsevier, vol. 155(C), pages 351-360.
    11. Bakker, Monique & Riezebos, Jan & Teunter, Ruud H., 2012. "Review of inventory systems with deterioration since 2001," European Journal of Operational Research, Elsevier, vol. 221(2), pages 275-284.
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    2. Sebatjane, Makoena, 2022. "The impact of preservation technology investments on lot-sizing and shipment strategies in a three-echelon food supply chain involving growing and deteriorating items," Operations Research Perspectives, Elsevier, vol. 9(C).
    3. Sebatjane, Makoena & Adetunji, Olufemi, 2020. "A three-echelon supply chain for economic growing quantity model with price- and freshness-dependent demand: Pricing, ordering and shipment decisions," Operations Research Perspectives, Elsevier, vol. 7(C).
    4. Cynthia Griselle De-la-Cruz-Márquez & Leopoldo Eduardo Cárdenas-Barrón & J. David Porter & Imelda de Jesús Loera-Hernández & Neale R. Smith & Armando Céspedes-Mota & Gerardo Treviño-Garza & Rafael Ern, 2023. "An Inventory Model for Growing Items When the Demand Is Price Sensitive with Imperfect Quality, Inspection Errors, Carbon Emissions, and Planned Backorders," Mathematics, MDPI, vol. 11(21), pages 1-45, October.
    5. Amir Hossein Nobil & Erfan Nobil & Leopoldo Eduardo Cárdenas-Barrón & Dagoberto Garza-Núñez & Gerardo Treviño-Garza & Armando Céspedes-Mota & Imelda de Jesús Loera-Hernández & Neale R. Smith, 2023. "Economic Order Quantity for Growing Items with Mortality Function under Sustainable Green Breeding Policy," Mathematics, MDPI, vol. 11(4), pages 1-21, February.
    6. Abolfazl Gharaei & Alireza Amjadian & Ali Shavandi & Amir Amjadian, 2023. "An augmented Lagrangian approach with general constraints to solve nonlinear models of the large-scale reliable inventory systems," Journal of Combinatorial Optimization, Springer, vol. 45(2), pages 1-37, March.
    7. Amir Hossein Nobil & Erfan Nobil & Leopoldo Eduardo Cárdenas-Barrón & Dagoberto Garza-Núñez & Gerardo Treviño-Garza & Armando Céspedes-Mota & Imelda de Jesús Loera-Hernández & Neale R. Smith, 2023. "Economic Growing Quantity Model with Mortality in Newborn Items and Inhibition Cost of Ammonia Production under All-Units Discount Policy," Sustainability, MDPI, vol. 15(10), pages 1-16, May.

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