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A new order splitting model with stochastic lead times for deterioration items

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  • Zeinab Sazvar
  • Mohammad Reza Akbari Jokar
  • Armand Baboli

Abstract

In unreliable supply environments, the strategy of pooling lead time risks by splitting replenishment orders among multiple suppliers simultaneously is an attractive sourcing policy that has captured the attention of academic researchers and corporate managers alike. While various assumptions are considered in the models developed, researchers tend to overlook an important inventory category in order splitting models: deteriorating items. In this paper, we study an order splitting policy for a retailer that sells a deteriorating product. The inventory system is modelled as a continuous review system (s, Q) under stochastic lead time. Demand rate per unit time is assumed to be constant over an infinite planning horizon and shortages are backordered completely. We develop two inventory models. In the first model, it is assumed that all the requirements are supplied by only one source, whereas in the second, two suppliers are available. We use sensitivity analysis to determine the situations in which each sourcing policy is the most economic. We then study a real case from the European pharmaceutical industry to demonstrate the applicability and effectiveness of the proposed models. Finally, more promising directions are suggested for future research.

Suggested Citation

  • Zeinab Sazvar & Mohammad Reza Akbari Jokar & Armand Baboli, 2014. "A new order splitting model with stochastic lead times for deterioration items," International Journal of Systems Science, Taylor & Francis Journals, vol. 45(9), pages 1936-1954, September.
  • Handle: RePEc:taf:tsysxx:v:45:y:2014:i:9:p:1936-1954
    DOI: 10.1080/00207721.2012.759301
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    References listed on IDEAS

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    1. Mahmood Vahdani & Zeinab Sazvar & Kannan Govindan, 2022. "An integrated economic disposal and lot-sizing problem for perishable inventories with batch production and corrupt stock-dependent holding cost," Annals of Operations Research, Springer, vol. 315(2), pages 2135-2167, August.

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