应用单亲遗传算法进行大规模UCAVs任务分配

在应用GA求解大规模无人作战飞机(UCAVs)任务分配这个典型组合优化问题时,需要使用描述问题直观的序号编码方式,但由于传统的交叉、变异算子操作复杂,因而进化效率不高.针对上述的不足,提出了一种单亲遗传算法,采用序号编码,使用基因换位等遗传算子,简化了遗传操作.通过对单亲遗传算法、传统遗传算法求解该问题所得的结果作了详细的比较,证明了单亲遗传算法在寻优效率上的优越性.

Application of SPGA to Large Scale Task Assignment of UCAVs

Genetic algorithm with sequence code is indispensable to solving the typical combinatorial optimization problem of large scale task assignment for UCAVs,but the evolutional efficiency is lower owing to complex operations of traditional crossover and mutation operator.Considering the above deficiency of GA using ordinal strings,this paper proposes a Single Parent Genetic Algorithm(SPGA) that that uses ordinal strings and introduces some particular genetic operators such as gene exchange.Comparison of results comes from SPGA and GA show the efficiency of SPGA.