Metaheuristic Optimization for Hospital Sterilisation and Decontamination Services.

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.