Publisher

IOCSCIENCEIOCSCIENCE

Journal VertexVertex Abstract

This research explores the optimization of evacuation routes amid volcanic eruptions around Mount Sinabung, employing sophisticated pathfinding algorithms the Bellman Ford and Floyd Warshall algorithms. Leveraging diverse datasets encompassing geographical, demographic, and historical information, the study aims to identify optimal evacuation paths considering factors such as terrain conditions, population distribution, and real-time adaptability. The studys methodology involves the integration of geospatial data, historical eruption records, and infrastructure details into structured graph representations, enabling algorithmic route computations. Comparative analyses of the Bellman Ford and Floyd Warshall algorithms highlight their strengths, limitations, and applicability in dynamic volcanic scenarios, offering nuanced insights into their performance. The findings reveal optimized evacuation routes that prioritize safety, efficiency, and inclusivity, catering to diverse demographic needs. Additionally, future research directions outlined for refining pathfinding algorithms stress the importance of interdisciplinary collaboration, technological advancements, and community-centric approaches in enhancing disaster preparedness and response strategies. This research contributes to the evolving landscape of disaster management by offering evidence-based insights, actionable recommendations, and a roadmap for policymakers, emergency responders, and local authorities.

Conclusion

The analysis successfully identified optimal evacuation routes considering terrain, population, and real-time adaptability.The study emphasized the importance of dynamic adaptability in evacuation planning, allowing for adjustments based on changing volcanic conditions.These findings offer a blueprint for strategic resource allocation, policy formulation, and community engagement to minimize the impact of volcanic disasters and safeguard lives.

Future Research

Future research should focus on integrating real-time data streams from IoT devices and social media to enhance the algorithms responsiveness to changing conditions. Furthermore, developing dynamic risk assessment models that continuously evaluate volcanic hazards and their impact on evacuation routes is crucial. Finally, exploring machine learning techniques to optimize routes dynamically, considering a broader range of parameters, will improve route efficiency and adaptability, ultimately contributing to more effective disaster response strategies and community resilience. These advancements will require interdisciplinary collaboration and a commitment to community-centric approaches to ensure the development of robust and practical solutions for mitigating the risks associated with volcanic eruptions.

Metadata

File size	399.14 KB
Pages	14
DMCA	Report