计算机工程与应用 ›› 2021, Vol. 57 ›› Issue (14): 259-266.DOI: 10.3778/j.issn.1002-8331.2003-0412

• 工程与应用 • 上一篇    下一篇

双向蚁群算法的智能消防疏散图路径规划

张苏英,郭宝樑,陈灵芝,刘慧贤   

  1. 河北科技大学 电气工程学院,石家庄 050000
  • 出版日期:2021-07-15 发布日期:2021-07-14

Path Planning of Intelligent Fire Evacuation Map Based on Bidirectional Ant Colony Algorithm

ZHANG Suying, GUO Baoliang, CHEN Lingzhi, LIU Huixian   

  1. College of Electrical Engineering, Hebei University of Science and Technology, Shijiazhuang 050000, China
  • Online:2021-07-15 Published:2021-07-14

摘要:

当前我国正处在城市发展高速时期,综合建筑不断涌现,这时可根据火灾实时信息自动调整疏散路径的智能消防疏散图应运而生。路径规划算法是智能消防疏散图的重点研究方向之一。针对智能消防疏散图需结合火场信息动态规划路径等问题,提出了一种改进双向蚁群算法。添加了双向搜索策略,提高了算法全局搜索能力;结合A*算法改进了初始信息素分布,减小了算法初期搜索盲目性;改进了信息素更新策略,提高了算法收敛速度;结合火场信息和转向惩罚系数对算法蒸发系数、启发函数和转移概率进行改进,降低了陷入局部最优风险,提高了算法搜索效率和路径平滑性,并有效避开了火灾影响区域。通过仿真验证了算法有效性。

关键词: 综合建筑, 消防疏散图, 蚁群算法, 路径规划

Abstract:

China is currently in a period of rapid urban development, the comprehensive buildings continue to emerge. At this time, an intelligent fire evacuation map that can automatically adjust the evacuation path based on real-time fire information emerges as the times require. Path planning algorithm is one of the key research directions of intelligent fire evacuation map. Aiming at the problems of intelligent fire evacuation maps that need to be combined with fire field information to dynamically plan paths, this paper proposes an improved bidirectional ant colony algorithm. First, this paper adds bidirectional search strategy to improve the algorithm’s global search capability. Then this paper combines with the A*algorithm to improve the initial pheromone distribution and reduces the blindness of the initial search of the algorithm. In order to improve the convergence speed of the algorithm, the pheromone update strategy is improved. Finally, this paper combines the fire scene information and steering penalty coefficient, improves algorithm evaporation coefficient, heuristic function and transition probability. The risk of the algorithm falling into the local optimum is reduced, improving the algorithm search efficiency and path smoothness, and effectively avoiding the fire affected area. Simulation results show the effectiveness of the algorithm.

Key words: comprehensive building, fire evacuation plans, ant colony algorithm, route plan