Optimization of Emergency Healthcare System with Priority Based Queuing Model and Dynamic Programming
Abstract
This study introduces a priority-based multi-class, multi-server accumulating priority queuing system designed to balance waiting times and resource utilization under both normal and high-demand conditions. Dynamic adjustment of priority rates ensures minimal delays for high-priority patients during peak periods while maintaining fairness across patient groups. System performance is evaluated using metrics such as queue length, priority accumulation, and a fairness index that capture complex, nonlinear interactions between resource allocation strategies and patient flow. Integration of these performance metrics strengthens the model’s ability to respond to real-world variability and ensures robust performance under unpredictable demand. Advanced queuing frameworks, including Markov-modulated and non-Markovian models, further reveal trade-offs between fairness and efficiency, providing additional insights into adaptive healthcare system design. Class-specific, metric-focused simulations validate system reliability and effectiveness. In addition, dynamic programming is employed to optimize resource allocation by balancing urgency and waiting time, thereby enhancing cost efficiency and fairness. Visualizations such as resource utilization plots and patient distribution graphs support informed and effective management decisions.
Keywords
- Dynamic programming
- Healthcare
- Heterogeneous waiting time distributions
- Multi-class Multi-server Accumulating Priority Queue
- Non-linear priority
- Simulation
Supporting Institution
Thanks
References
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Details
Primary Language
English
Subjects
Software Engineering (Other)
Journal Section
Research Article
Authors
Abdela Mohammed
*
0000-0003-1770-3709
Ethiopia
Early Pub Date
June 18, 2026
Publication Date
-
Submission Date
June 26, 2025
Acceptance Date
January 23, 2026
Published in Issue
Year 2026 Number: Advanced Online Publication
