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Inventory control in healthcare supply chain management using apriori and gravitational search algorithms

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  • J. Arul Valan
  • E. Baburaj

Abstract

Due to this kind of demand, healthcare supply chains (SC) need to keep high inventory levels to ensure high availability of medicines to save people's lives. We develop a method that effectively utilises the data mining concepts as well as gravitational search algorithm (GSA) for optimal inventory control. The proposed method consists of two key functions, mining association rules for inventory and choosing SC cost-impact rules. Initially, the association rules are mined from EMA-based healthcare inventory data. After that, SC cost-impact rules are chosen for every SC member using GSA. The obtained SC cost-impact rules will possibly signify the future state of inventory in any SC member. Furthermore, the level of holding or reducing the inventory can be determined from the SC cost-impact rules. Thus, the SC cost-impact rules that are derived using the proposed method greatly facilitate optimal inventory control and hence make the supply chain management more effective.

Suggested Citation

  • J. Arul Valan & E. Baburaj, 2020. "Inventory control in healthcare supply chain management using apriori and gravitational search algorithms," International Journal of Logistics Systems and Management, Inderscience Enterprises Ltd, vol. 35(4), pages 511-525.
    • Handle: RePEc:ids:ijlsma:v:35:y:2020:i:4:p:511-525
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