Evaluation of PSO Algorithm Considering Obstacle Avoidance in Evacuation Guidance

Year 2022, Volume: 6 Issue: 3, 318 - 335, 30.09.2022

Tomofumi Matsuzawa , Akiyoshi Ishii

https://doi.org/10.31197/atnaa.1095309

Abstract

In recent years, IoT has been expected to provide support during natural disasters, and studies focusing on ant colony optimization (ACO) have been conducted for providing evacuation routes for evacuees.
We previously proposed a modified algorithm for ACO that improved on the slow convergence of ACO, but the problem with ACO-based evacuation is the time it takes the evacuees to reach a safe zone.

In this study, we proposed a route suggestion algorithm that improves particle swarm optimization (PSO) to reduce the time required for ACO evacuation, and compared the performance of ACO and the proposed PSO. We also proposed a method that combines ACO and PSO and evaluated its performance.

Keywords

ACO, PSO, Evacuation guidance, Natural disaster

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