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| Main Authors: | , , , |
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| Format: | Recurso digital |
| Language: | English |
| Published: |
Zenodo
2026
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| Subjects: | |
| Online Access: | https://doi.org/10.5281/zenodo.18296111 |
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Table of Contents:
- <p><strong>Autonomous Agent for Optimized Allocation and Routing of Water Trucks in Severe Drought Emergencies</strong></p> <p>This AGENT implements a hybrid Ant Colony Optimization algorithm with adaptive local search to solve the Vehicle Routing Problem with Time Windows (VRPTW) for emergency water trucking. Considers multiple water depots, heterogeneous fleet, social vulnerability prioritization, and deprivation costs. Operates in real-time, dynamically recalculating routes as new critical demands emerge.</p> <p><strong>Key Features:</strong> Multi-depot vehicle routing problem (MDVRP-TW); social cost vehicle routing; real-time route optimization; heterogeneous fleet management; GPS telemetry integration; mobile app for driver navigation; FIPA-ACL agent communication protocol.</p> <p><strong>Potential Impact:</strong> Can potentially reduce average response time in humanitarian water distribution, achieve operational cost savings through route optimization, and improve equity in service delivery to vulnerable populations in rural emergency contexts.</p> <p><strong>Technical Details:</strong> Python 3.11, microservices architecture, MQTT communication protocol, genetic algorithm solver. TRL 8 (demonstrated in operational environment). Reoptimization capability under 2 minutes for fleets up to 50 vehicles.</p> <p>Developed at Universidade Federal de Mato Grosso (UFMT) in collaboration with civil defense agencies, space research institutes, and telemetry providers.</p> <p><em>Part of this content may have been AI-generated under supervision by Daniel Thomaz Giacomelli Nunes Maciel.</em></p>