基于粒子群算法优化跨海大桥应急救援物资无人机调度

Optimization of unmanned aerial vehicles(uavs)emergency rescue material dispatching for cross-sea bridges using particle swarm algorithm optimization(PSAO)

为实现在灾害环境下对跨海大桥灾区的应急物资调度分配及缩短应急救援时间,假设应急救援的范围为50 km×50 km的二维平面内,将任务组的个数和粒子的维度设定相等,假设应急救援无人机的数量是应急救援任务数量的3倍,设定应急救援任务数量和应急救援无人机的数量,通过设置不同的救援信息(如受灾点位置、供应点无人机位置等),将粒子群算法(算法一)分别加入分组策略和自适应惯性权重策略来改进算法,分别形成新的算法二、三,将每组试验进行3次测试,取平均值,并推出最快运行时间。结果表明,算法二(粒子群算法加入分组策略)使得距离较短的任务归为同一任务组中,因此,粒子的纬度会变小,从而算法运行所用时间最短。随着救援任务与无人机数量的增加,分组策略的效果更好,能在不同程度上提高任务分配效率与缩短救援时间。

In order to realize the dispatching and distribution of emergency supplies to the disaster area of the cross-sea bridge and shorten the emergency rescue time under the disaster environment,this paper assumes that the scope of emergency rescue is within a two-dimensional plane of 50 km×50 km,sets the number of task groups and the dimension of particles equal,assumes that the number of emergency rescue drones is three times the number of emergency rescue tasks,sets the number of emergency rescue tasks and the number of emergency rescue drones,and improves the algorithm by Setting different rescue information(such as the location of the affected point,the location of the supply point drone,etc.),the particle swarm algorithm(Algorithm I)is improved by adding grouping strategy and adaptive inertia weighting strategy to the algorithm to form new Algorithms II and III respectively,and each group of experiments is tested three times to take the average value and introduce the fastest running time.The result show that Algorithm II(particle swarm algorithm adding grouping strategy)groups the tasks with shorter distances in the same task group.Therefore,the latitude of particles will become smaller,and thus the algorithm takes the shortest time to run.As the number of rescue tasks and Unmanned Aerial Vehicles(UAVs)increases,the grouping strategy is more effective and can improve the efficiency of task assignment and shorten the rescue time to different degrees.