复杂建筑火灾中的人员疏散路径多目标规划

针对复杂建筑火灾中的人员疏散动态路径优化策略问题，以火灾情境下的动态疏散网络数据模型为基础，结合网络流优化和群智能方法，构建以最短时间、最小风险水平和最大疏散容量为目标的路径优化模型.通过改进的自适应果蝇算法，实现了节点和路径容量受限的动态疏散路径规划.通过对所建模型的性能测试和疏散过程实验，验证了多目标路径优化模型的有效性.实验结果也反映了多目标路径规划策略更加贴近复杂建筑火灾中的人员疏散实际情况，对于规划不确定因素影响下的复杂空间疏散路径具有可行性.

Multi-objective Planning of Personnel Evacuation Route in Complex Building Fire

Aiming at the strategy of personnel evacuation dynamic path optimization in complex building fire， the path optimizing model with the shortest time， the maximum evacuation capacity and the minimum risk level as the optimization objective was constructed， which was based on the dynamic evacuation network data model in fire situation and combined with the network flow optimization and swarm intelligence method. Dynamic evacuation path planning with limited node and path capacity was realized by the modified adaptive fruit fly optimization algorithm. Through the performance test and evacuation process experiment on the established model， the effectiveness of the multi-objective path optimization model was verified. The experimental results also indicates that the multi-objective path planning strategy is closer to the evacuation practice in complex building fire. It is feasible for planning complex space evacuation path under the influence of uncertain factors.