基于蚁群算法的烟气中人员疏散路径选择优化

针对火灾烟气环境下的人员疏散问题，分析人员密度以及烟气能见度对疏散速度以及最佳疏散路径的影响。首先，得到烟气及人员密度对疏散速度的修正函数，并将该函数同蚁群算法的启发式信息函数进行耦合；其次，改进蚁群算法求解最佳路径的局限性，建立1种基于蚁群算法的人员疏散路径算法模型；最后，将算法模型应用于实例研究。研究结果表明:所提出的模型可较好地优化人员疏散路径，并进一步提高人员疏散效率。

Optimization of evacuation route selection for personnel in smoke environment based on ant colony algorithm

Aiming at the problem of personnel evacuation in the fire smoke environment, the influence of evacuation speed and optimal route affected by smoke and personnel density was analyzed. Firstly, the correction function of smoke and personnel density to the evacuation speed was obtained, and it was coupled with the heuristic information function of the ant colony algorithm. Secondly, the limitation for solving the optimal route of the ant colony algorithm was improved, and an algorithm model of personnel evacuation route based on the ant colony algorithm was established. Finally, this algorithm model was applied to the case study. The results showed that the proposed model could optimize the personnel evacuation route well and increase the efficiency of personnel evacuation to a higher degree.