An Intelligent Optimazitation Method for Evacuation Route Planning in the Occurrence of Natural Disasters

Abstract

This research aims to design and apply intelligent optimization methods using various algorithms to find disaster evacuation routes. The efficiency and effectiveness of evacuation routes are essential in disaster situations to ensure the safety of the affected residents. This research focuses on developing an intelligent optimization method utilizing the Multi Vertex Multi Goals (MVMG) scheme to find optimal evacuation routes. In this scheme, multiple starting points and evacuation destinations reflect the actual conditions on the ground. The Ant Colony Optimization (ACO) algorithm was chosen because of its superiority in finding optimal solutions in dynamic and complex conditions. This research also compares the performance of ACO with traditional algorithms, such as Dijkstra and Breadth-First Search (BFS). The test results show that ACO consistently achieves the lowest evacuation time and the highest efficiency compared to the other two algorithms. In addition, this research opens opportunities for further research by considering complex factors, including traffic congestion and disaster-prone areas, to improve the robustness and application of optimization algorithms in more realistic and dynamic scenarios.

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