基于火场预测和多出口决策的协同进化救援路径优化方法

Co-evolutionary rescue path optimization method based on fire prediction and multi-exit decision-making

为给深入火场救援的消防员提供最佳救援路线,掌握营救和自救时机,通过改变涟漪规则、动态调整扩散速度、多出口决策设置来改进基于涟漪扩散算法(RSA)协同进化路径优化方法(CEPO)。基于火场预测和多出口决策提出协同进化救援路径优化(CERPO)方法,并以湖北某校教学楼火灾扩散仿真模拟为背景,在不同时间节点情境下规划最佳救援往返路径并比较路径异同,与D算法对比验证CERPO有效性和灵活性。研究结果表明:CERPO能基于火灾预测提前避障规划最佳路径,并在第500 s情境下及时启动多出口决策,规划新的撤离路径;CERPO与传统算法相比可避免绕路,提高消防救援效率,研究结果可为救援路径规划提供参考。

In order to provide the best rescue path for the firefighters who go deep into the fire to rescue,and master the timing of rescue and self-rescue,a co-evolutionary rescue path optimization(CERPO)method was proposed on the basis of fire prediction and multi-exit decision-making.The co-evolution path optimization(CEPO)method based on the ripple spreading algorithm(RSA)was improved by changing the ripple rules,dynamically adjusting the diffusion speed,and setting the multi-exit decision-making.Taking the fire diffusion simulation of a teaching building in an university of Hubei as the background,the best rescue paths were planned at different time nodes and the similarities and differences of the paths were compared,and the effectiveness and flexibility of CERPO were verified by comparing with the D algorithm.The results showed that CERPO could avoid the obstacles in advance based on fire prediction,plan the best path,and initiate multi-exit decision-making in time to plan a new evacuation path in the 500 s situation.Compared with traditional algorithms,CEPRO can avoid detour and improve the fire rescue efficiency,which provides reference for the rescue path planning.