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Lot sizing and lead time decisions in production/inventory systems

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  • Noblesse, Ann M.
  • Boute, Robert N.
  • Lambrecht, Marc R.
  • Van Houdt, Benny

Abstract

Traditionally, lot sizing decisions in inventory management trade-off the cost of placing orders against the cost of holding inventory. However, when these lot sizes are to be produced in a finite capacity production/inventory system, the lot size has an important impact on the lead times, which in turn determine inventory levels (and costs). In this paper we study the lot sizing decision in a production/inventory setting, where lead times are determined by a queueing model that is linked endogenously to the orders placed by the inventory model. Assuming a continuous review (s, S) inventory policy, we develop a procedure to obtain the distribution of lead times and the distribution of inventory levels, when lead times are endogenously determined by the inventory model. This procedure allows to determine the optimal inventory parameters within the class of (s, S) policies that minimize the expected ordering and inventory related costs over time. We numerically show that ignoring the endogeneity of lead times may lead to inappropriate lot sizing decisions and significantly higher costs. This cost discrepancy is very outspoken if the lot size based on the economic order quantity deviates significantly from desirable production lot sizes. In these cases, the endogenous treatment of lead times is of particular importance.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:proeco:v:155:y:2014:i:c:p:351-360
    DOI: 10.1016/j.ijpe.2014.04.027
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    References listed on IDEAS

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    2. Daniela Favaretto & Alessandro Marin & Marco Tolotti, 2021. "A data-driven and risk-based prudential approach to validate the DDMRP planning and control system," Working Papers 09, Department of Management, Università Ca' Foscari Venezia.
    3. Gharaei, Abolfazl & Almehdawe, Eman, 2020. "Economic growing quantity," International Journal of Production Economics, Elsevier, vol. 223(C).
    4. Qiu, Ruozhen & Sun, Minghe & Lim, Yun Fong, 2017. "Optimizing (s, S) policies for multi-period inventory models with demand distribution uncertainty: Robust dynamic programing approaches," European Journal of Operational Research, Elsevier, vol. 261(3), pages 880-892.
    5. Jalali, Hamed & Carmen, Raïsa & Van Nieuwenhuyse, Inneke & Boute, Robert, 2019. "Quality and pricing decisions in production/inventory systems," European Journal of Operational Research, Elsevier, vol. 272(1), pages 195-206.
    6. Hernan Caceres & Dongchen Yu & Alexander Nikolaev, 2018. "Evaluating shortfall distributions in periodic inventory systems with stochastic endogenous demands and lead-times," Annals of Operations Research, Springer, vol. 271(2), pages 405-427, December.
    7. Heydari, Jafar & Mahmoodi, Mansour & Taleizadeh, Ata Allah, 2016. "Lead time aggregation: A three-echelon supply chain model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 89(C), pages 215-233.

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