Hospitals often face challenges in effectively managing critical resources such as ICU beds, ventilators, medical staff, and operating rooms. During peak times like flu seasons or pandemics, inefficient allocation can lead to increased patient mortality and operational strain. This project aims to formulate an optimization model to dynamically allocate resources based on patient severity, predicted admission rates, and resource availability. Real-world constraints such as staff availability, equipment downtime, and emergency patient arrivals must be incorporated.
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To develop an optimization algorithm that dynamically adjusts resource allocation in hospitals based on real-time patient demand, ensuring optimal patient outcomes and improved hospital efficiency
Chaltienne/Optimization
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To develop an optimization algorithm that dynamically adjusts resource allocation in hospitals based on real-time patient demand, ensuring optimal patient outcomes and improved hospital efficiency
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