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Multi-Agent Simulation for Ambulance Allocation and Routing After Natural Disasters

Learn how multi-agent systems, Voronoi diagrams, and genetic algorithms optimize ambulance allocation and routing in disaster scenarios, reducing response times by 36.7%.

Effective disaster response requires rapid ambulance allocation and optimized routing to save lives. A novel multi-agent system integrates smart city facilities, Voronoi diagrams, and advanced algorithms to improve emergency response, reducing ambulance response times by 36.7%.
In this post, we explore how these innovative methods, including genetic algorithms like NSGA-II, are transforming disaster management and optimizing rescue operations.
<hr>
<h4>Assignment Instructions</h4>
Title: Multi-Agent Simulation of Allocating and Routing Ambulances Under Condition of Street Blockage After Natural Disaster.
Objective: Develop a multi-agent system to:
<ol>
<li>Allocate ambulances to wounded locations using Voronoi diagrams.</li>
<li>Route ambulances efficiently, minimizing travel time and distance using the NSGA-II algorithm.</li>
<li>Incorporate real-time updates of blocked streets via smart city volunteer reports.</li>
</ol>
Methodology:
<ul>
<li>Utilize Voronoi diagrams to define service areas.</li>
<li>Apply simulated annealing for optimized ambulance allocation.</li>
<li>Implement NSGA-II for multi-objective route optimization.</li>
<li>Collect real-time traffic updates from local volunteers.</li>
</ul>
<hr>
<h4>Key Insights and Tips</h4>
<ol>
<li>
Why Multi-Agent Systems? Multi-agent systems enable decentralized coordination, allowing ambulances to act autonomously while sharing real-time data about street blockages and wounded locations.
</li>
<li>
How Voronoi Diagrams Help: These diagrams allocate service areas based on proximity and population density, ensuring equitable distribution of emergency resources.
</li>
<li>
Role of NSGA-II: This genetic algorithm minimizes ambulance travel time and route length, dynamically adjusting for real-time changes in road conditions.
</li>
<li>
Smart City Contributions: Volunteers provide vital real-time information about blocked streets, enhancing decision-making and reducing delays.
</li>
</ol>
<hr>
<h4>Real-World Example</h4>
The system was tested in Tehran’s District 5, using two emergency centers and real-time street blockage updates from volunteers. The results:
<ul>
<li>Reduced ambulance response times by 36.7%.</li>
<li>Improved alignment between supply (ambulances) and demand (wounded locations), achieving a supply-demand error rate of 0.1601.</li>
</ul>

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Multi-Agent Simulation for Ambulance Allocation and Routing After Natural Disasters

Learn how multi-agent systems, Voronoi diagrams, and genetic algorithms optimize ambulance allocation and routing in disaster scenarios, reducing response times by 36.7%.

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