Evacuation Route Optimization for Volcanic Hazards Using Ant Colony Metaheuristics and Mobile GIS - Aziz, Muhammad; Prabowo, Basit Adhi (International Journal of Electronics and Communications Systems, 2025)
Effective evacuation planning in volcanic areas requires real-time spatial awareness, community integration, and algorithm validation. This study aims to introduce SVACO-GIS, an innovative system that integrates Ant Colony Optimization (ACO), Geographic Information Systems (GIS), and the Sister Village framework to optimize evacuation routes under volcanic hazard conditions by identifying safe and efficient evacuation routes and strengthening community-based evacuation planning. The research applies the SVACO-GIS approach using a multi-parameter asymmetric heuristic matrix that incorporates slope, river distance, red zone exclusion, shelter readiness, and population density to better represent real-world constraints and safety priorities. Simulation results show that the application of SVACO-GIS produces structurally different evacuation route patterns compared to the shortest path-based approach. Routes optimized with SVACO-GIS consistently avoid major river corridors and areas with high slope gradients previously identified as high-risk zones in the context of Mount Merapi eruptions. The resulting evacuation network is directional and does not allow movement back toward zones with higher hazard levels, aligning with the one-way evacuation principle of the Sister Village system. The integration of local wisdom with intelligent spatial computing improves evacuation efficiency and sets a replicable standard for disaster preparedness in other high-risk geographies. These findings suggest that SVACO-GIS can support more informed decision-making, strengthen the resilience of vulnerable communities, and guide the development of intelligent evacuation systems in volcanic regions in the future