基于人工蜂群算法的疏散运动仿真

Evacuation Motion Simulation Based on Artificial Bee Colony Algorithm

针对原始人工蜂群算法在人群疏散仿真中存在的早熟停滞问题,提出一种基于种群划分思想的新型蜂群算法。以种群划分为基础,利用多种群协同进化机制扩展求解的多样性,防止算法陷入局部最优。以ACIS/HOOPS为平台搭建3D仿真系统,对改进算法进行人群疏散仿真及对比分析,结果表明,与原始算法相比,该算法在精度和收敛速度上明显提升。与粒子群优化算法相比,该算法能够实现人群疏散的均衡分布,提高应急疏散的效率。

According to the premature stagnation of original Artificial Bee Colony（ABC） algorithm in evacuation motion simulation, an improved algorithm based on the thought of population dividing is proposed. Multi-species cooperation mechanism is used to extend solution＇s diversity in order to prevent sinking into local optimum solutions. 3D simulation system is built based on ACIS/HOOPS to make evacuation simulation and comparison analysis on the proposed algorithm. The algorithm can improve accuracy and convergence speed compared with original algorithm, implement even distribution of population evacuation and improves the efficiency compared with Particle Swarm Optimization（PSO） algorithm according to the result of experiments.