A dynamic and intelligent decision-making framework for a platelet inventory-distribution network

Sara Cheraghi, Abdorrahman Haeri () and Seyed Farid Ghannadpour
Additional contact information
Sara Cheraghi: Iran University of Science and Technology
Abdorrahman Haeri: Iran University of Science and Technology
Seyed Farid Ghannadpour: Iran University of Science and Technology

Operational Research, 2025, vol. 25, issue 3, No 6, 61 pages

Abstract: Abstract Platelets over-ordering by hospitals is problematic and causes unnecessary wastage and costs of storage and purchase on one side and cost of shortage on the other side. This paper pioneers the design of a dynamic and intelligent scheme for platelets inventory-distribution policy which addresses the over-ordering concern using information about hospitals’ demand, orders, and their honesty in placing orders. Hospitals’ honesty affects the priority of hospitals to receive their orders. Employing artificial intelligence, the hospitals’ performance is analyzed by an intelligent agent in a deep reinforcement learning framework to make purchase and distribution decisions adaptable to the uncertain and dynamic environment. The dynamic mechanism modifies orders, transfers and priorities, and contributes to the fair distribution of platelets among hospitals. Besides several test instances, the practical application of the proposed framework is substantiated through a real topology. The computational results of the proposed scheme highlight cost savings of up to 13.68% and 64.10% compared to two approaches taken from the literature as benchmarks.

Keywords: Inventory-distribution; Platelets; Deep reinforcement learning; Rolling planning horizon (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s12351-025-00943-z Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:operea:v:25:y:2025:i:3:d:10.1007_s12351-025-00943-z

Ordering information: This journal article can be ordered from
https://www.springer ... search/journal/12351

DOI: 10.1007/s12351-025-00943-z

Access Statistics for this article

Operational Research is currently edited by Nikolaos F. Matsatsinis, John Psarras and Constantin Zopounidis

More articles in Operational Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().