Performance Comparison And Application Of Swarm Intelligence Algorithms In Crowd Evacuation

With the improvement of computer computing speed and the development of swarm intelligence algorithms, more and more swarm intelligence algorithms are used in the research of crowd evacuation. Firstly, some typical swarm intelligence algorithms are introduced. And their performances and applicable scenarios are compared and analyzed. Based on the analysis of various swarm intelligence algorithms, a new crowd evacuation model based on swarm intelligence algorithm is proposed in this paper. This model is based on dynamic grouping principle, driven by particle swarm optimization in microscopic perspective and artificial bee colony algorithm in macroscopic perspective. It fully combines the advantages of particle swarm optimization (PSO) to simulate the crowd more realistically with the advantages of artificial bee colony algorithm for global optimization. This proposed model also has better computational convergence, which can provide a professional basis for crowd evacuation.