改进蚁群算法的火灾环境疏散路径规划研究

doi:10.3778/j.issn.1002-8331.2310-0416

摘要/Abstract

摘要： 针对建筑物火灾人员疏散问题，以保证火灾人员安全撤离为目标，提出火灾环境下改进蚁群算法的路径规划模型。构建方向性信息函数，当搜索方向靠近目标节点，方向性信息函数的值增大使信息素差异化；根据火灾影响程度建立火灾等级函数，使转移概率随着火灾等级的增大而减小，减少蚁群寻路的盲目性；通过分析火灾影响因素建立等效长度并构建启发函数，避免陷入局部最优；结合火灾等级函数自适应调整信息素挥发系数，加快了火灾路径信息素挥发速度，提升算法全局搜索能力；同时在信息素更新策略中引入奖惩系数和模糊控制，提升疏散系统的鲁棒性以及路径平滑度，并对全局信息素进行限制，以平衡算法的局部开发与全局搜索能力。经仿真实验验证，改进的蚁群算法在有无火灾的情况下都能高效地规划出疏散路线。

关键词: 蚁群算法, 方向性信息函数, 等效长度, 模糊控制, 火灾人员疏散

Abstract: Aiming at the problem of building fire personnel evacuation, a path planning model with improved ant-colony algorithm is proposed to ensure the safety of fire personnel evacuation.When the search direction is close to the target node, the increase of the value of the directional information function makes the pheromone different. According to the fire impact degree, the fire grade function is established, so that the transfer probability decreases with the increase of the fire grade, and the blindness of the ant colony in finding the way is reduced. By analyzing the influence factors of fire, the equivalent length is established and the heuristic function is constructed to avoid falling into the local optimal. The volatili-zation coefficient of pheromone is adjusted adaptively with the fire grade function to accelerate the volatilization rate of the fire path pheromone and improve the global search ability of the algorithm. At the same time, the reward and punishment coefficient and fuzzy control are introduced in the pheromone updating strategy to improve the robustness and path smoothness of the evacuation system, and the global pheromone is restricted to balance the local development and global search ability of the algorithm. The simulation results show that the improved ant colony algorithm can efficiently plan evacuation routes in the case of fire or not.

Key words: ant colony algorithm, directional information function, equivalent length, fuzzy control, fire evacuation

杜云, 刘小雨, 贾科进, 丁力, 黄公发. 改进蚁群算法的火灾环境疏散路径规划研究[J]. 计算机工程与应用, 2024, 60(8): 309-319.

DU Yun, LIU Xiaoyu, JIA Kejin, DING Li, HUANG Gongfa. Research on Evacuation Path Planning in Fire Environment with Improved Ant Colony Algorithm[J]. Computer Engineering and Applications, 2024, 60(8): 309-319.

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