用群智能算法确定井下火灾多救护队最优路径

确定最优应急救援路径是应对矿井火灾的首要任务。通过判断井巷可通行性、确定井巷通行难易度系数，解算了井巷当量长度，构建了基于多救护队的井下火灾救援路径模型。依据粒子群算法和蚁群算法的优点，提出了混合策略，即利用粒子群算法搜索蚁群算法参数α、β、ρ，再反馈到蚁群算法中，对多救护队最优救援路径进行搜索。通过MATLAB软件平台，利用该混合算法求解实例中最优救援路径，即当量长度最短的路径，为矿井事故预案救援和井下人员应急逃生提供理论依据。

Determination of Underground Mine Fire Optimal Path of Multi Rescue Teams by Swarm Intelligence Algorithm

Determining the optimal emergency rescue path is the primary task to deal with the mine fire.The equivalent length of roadway was calculated and the mathematical model of mine fire rescue path based on multi ambulance corps was built by judging the roadway passable resistance and the access difficulty coefficient.Meanwhile，a hybrid strategy has been proposed that based on merits of PSO and ACO-using，PSO was used to search parameters α，β，ρ of ACO，then back to ACO and search for optimal rescue path of multi rescue teams.Through the MATLAB software platform and using this hybrid algorithm，the optimal rescue path，the shortest path of equivalent length，was gained.It provided a theoretical basis for the mine accident rescue plan and the emergency escape plan of underground staffs.