基于仿生算法的灾后救援路径选择

Rescue path selection based on a bio-inspired algorithm

为解决应急物流管理中的路径选择问题,综合考虑了运输时间、运输距离和路径复杂性等因素,建立了灾后救援的路径选择模型.在灾难发生后,路径中的运输速度将被灾难扩展深深影响,特别是在洪水、飓风等灾难中,将在时间和空间上逐渐扩展,因此将运输速度设定为随着时间而连续递减的函数.针对问题性质,提出了多头绒泡菌算法来解决这个问题.多头绒泡菌算法不同于其他的仿生算法,可以100%找到最优路径.案例研究表明:利用该方法进行灾后救援路径选择,能够有效获得最优路径.

After a disaster, the travel speed will be greatly affected by disaster extension especially under some disasters like hurricane and flood that will extend gradually in time and space, so the travel speed is set to a continuous decrease function with respect to time. To solve the route selection problem in emergency logistics management, the travel time, the travel distance and the path complexity are taken into consideration. The rescue path selection model is established. For the nature of the problem, a novel bio-inspired algorithm is proposed to solve this problem. Unlike other bionic algorithms which can only converge to the optimal path with a certain probability, physarum algorithm can find the optimal path to 100%. A case study shows that the method can effectively obtain the optimal path for rescue path selection.