Aggregation and Adjustment mechanisms for disaster relief task allocation with uneven distribution

The use of unmanned aerial vehicles (UAVs) to perform disaster relief task is becoming more and popular. Generally, UAVs for rescuing are required be heterogeneous, since the types rescue missions diverse. There many researches on allocation heterogeneous UAVs, in which they setup tasks randomly distributed when simulation. However, most cases distribution regular rather than random. Therefore, we a set special scenarios simulate real tasks, where concentrate few small areas others randomly. LAL algorithm an appropriate alternative deal with assignment problems completely distributed, but bit poor performance above mentioned. In order obtain better results, this paper proposes three algorithms based such scenarios. They Aggregation-LAL (A-LAL) using aggregation mechanism, Dynamic Adjustment-LAL (DA-LAL) dynamic adjustment mechanism Aggregation Adjustment (AA-LAL) algorithms.Through experiments NetLogo simulation environment, proposed evaluated. result shows improvements, average 5% obtained by AA-LAL, our compared existing algorithms. Note: project funding information updated.