Metaheuristic optimization for hospital sterilisation and decontamination services

Davies, Thomas, England, Tracey J., Behrens, Doris A. and Gartner, Daniel ORCID: https://orcid.org/0000-0003-4361-8559 2025. Metaheuristic optimization for hospital sterilisation and decontamination services. Presented at: 20th World Congress on Medical and Health Informatics, Taipei, Taiwan, 9-13 August 2025. Published in: Househ, Mowafa S., Ul Abideen Tariq, Zain, Al-Zubaidi, Mahmood, Shah, Uzair and Huesing, Elaine eds. MEDINFO 2025 — Healthcare Smart × Medicine Deep. IOS Press, pp. 881-885. 10.3233/shti250966

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Abstract

Hospital Sterilization and Decontamination Units (HSDUs) play a critical role in ensuring the safe and efficient decontamination of surgical instruments to prevent healthcare-associated infections. This paper presents a mathematical modeling approach using Discrete Event Simulation (DES) to optimize staffing schedules within HSDUs at a district general hospital using Metaheuristic Optimization. The objective is to identify the optimal number of staff required to meet service demands while maintaining operational efficiency. A Greedy Heuristic and Tabu Search are employed to determine staffing levels that meet specific performance targets, including decontaminating at least 99% of items within the target time. Results showed that the Tabu Search algorithm significantly outperforms the Greedy Heuristic while maintaining 99% of items decontaminated within the required time. Our findings suggest that Tabu Search provides a more reliable and efficient method for optimizing staffing in HSDUs. Further work is recommended to explore cost implications of staffing decisions.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Publication
Status:	Published
Schools:	Schools > Mathematics
Publisher:	IOS Press
ISBN:	9781643686080
Date of First Compliant Deposit:	19 August 2025
Last Modified:	19 Aug 2025 11:17
URI:	https://orca.cardiff.ac.uk/id/eprint/180558

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