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An Artificial Immune System Approach for a Multi-compartment Queuing Model for Improving Medical Resources and Inpatient Bed Occupancy in PandemicsBELCIUG, S. , BEJINARIU, S.-I. , COSTIN, H.
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artificial intelligence, evolutionary computation, hospitals, optimization, queueing analysis
optimization(22), inspired(12), nature(9), algorithms(9), intelligence(8), artificial(7), systems(6), gorunescu(6), algorithm(6), selection(5)
Blue keywords are present in both the references section and the paper title.
About this article
Date of Publication: 2020-08-31
Volume 20, Issue 3, Year 2020, On page(s): 23 - 30
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2020.03003
Web of Science Accession Number: 000564453800003
SCOPUS ID: 85090354940
In the context of the Covid-19 pandemic the pressure that is put on the medical systems is increasing exponentially. Healthcare systems resources are in general scarce, and hence they require policies that ensure the optimal usage of beds and utilization costs. The aim of this study is to explore how artificial immune system approaches for a multi-queuing model may aid the hospital managers improve their resources. The proposed system outlines the route of Covid-19 patients in the intensive care unit (ICU), the compartmental model proposes a reasonable composition of the ICU, considering the queuing parameters, while the artificial immune system optimizes the needed resources (beds plus associated costs). The methodology was demonstrated through a simulation based on real data collected from official sources.
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