https://github.com/gitsiddharth/hospitaled_simulation
Hospital ED Simulation is an AnyLogic-based discrete event simulation of an emergency department, enhanced with reinforcement learning for optimal resource allocation.
https://github.com/gitsiddharth/hospitaled_simulation
anylogic-simulation graphviz-dot latex-document mermaidjs
Last synced: 3 months ago
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Hospital ED Simulation is an AnyLogic-based discrete event simulation of an emergency department, enhanced with reinforcement learning for optimal resource allocation.
- Host: GitHub
- URL: https://github.com/gitsiddharth/hospitaled_simulation
- Owner: GitSiddharth
- License: gpl-2.0
- Created: 2025-03-25T10:59:29.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2025-03-25T11:27:59.000Z (3 months ago)
- Last Synced: 2025-03-25T12:21:34.603Z (3 months ago)
- Topics: anylogic-simulation, graphviz-dot, latex-document, mermaidjs
- Language: TeX
- Homepage:
- Size: 284 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# hospitalED_simulation
## How to Use This Project
1. **AnyLogic Model:**
Open the `.alp` file in the `simulation/` folder using AnyLogic Personal Edition (or a compatible version). Run the simulation to observe the ED process and the impact of RL-based decisions.2. **Documentation:**
- The PDF flowchart provides an overview of the process flow.
- The LaTeX file contains the research paper that describes the model, methodology, and results.3. **Customization:**
You can modify simulation parameters (e.g., arrival rates, treatment durations, severity thresholds) directly in the AnyLogic model. The RL agent’s logic is implemented via custom Java code within the model.## Requirements
- **AnyLogic Personal Edition** (or compatible version)
- Basic knowledge of Java for custom code modifications
- LaTeX distribution (optional, for compiling the research paper)## License
This project is licensed under the [MIT License](LICENSE).
## Contact
For any questions or contributions, please contact Siddharth Jaiswal at [email protected]