Increasing the Efficiency of Using CCU Beds of Hospitals through Optimization and Combination of Genetic Algorithm and Imperialist Competitive

Hospitals as the most important consumer of resources in healthcare section are highly sensitive to maximum consumption of minimum existing resources. In the recent two decades, computer data processing to extract knowledge and improve utilization of resources has attracted the attention of organizations. In this study, allocation of CCU beds in Shahid Faghihi Hospital of Shiraz is investigated through optimizing and combining Genetic Algorithm (GA) and Imperialist Competitive Algorithm (ICA).
In this analytic cross-sectional study, patients were monitored through optimization and combination of genetic algorithm and imperialist competitive and allocated to CCU beds in the spring of 2016. To this end, number of patients, number of beds, number of doctors and vital signs of patients were used as input and configuration of patients and allocation optimization were considered as output. MATLAB 2012 was used to analyze data.
Results of this study show that ICA is more efficient compared to GA in optimization of allocating CCU beds to patients. Moreover, the hybrid algorithm obtained from combination of ICA and GA is more efficient than ICA.
In the process of this study, priorities of patient's hospitalization and also manner of hospitalization were determined and suggestions for allocation of beds to patients were presented.