摘要
针对战场环境的多目标、多任务以及无人机能力有限等特点,设计了一种适应于多目标、多无人机、多任务种类的无人机群协同多任务分配模型。结合该模型以及其中的任务偏序约束、协同任务约束、无人机能力约束等约束条件提出了基于任务序列的遗传算法染色体编码方法,和基于同类任务的遗传算法交叉、变异算子。该方法利用遗传算法的全局搜索优化解特点,对无人机群的协同任务分配进行优化。仿真试验表明该方法能够保证满足任务分配约束条件的基础上使任务的分配更加优化。
A cooperative multi-task assignment problem （CMPAT） model is designed for battlefield environment of multi-objective, multi-task and limited capacity of unmanned aerial vehicle （UAV）. According to the task sequence constraint, the cooperative task constraint, and the UAV capacity constraint in the CMPAT model, the chromosome coding method based on task sequence and the cross and disturbance operators based on same category tasks changing are proposed. With the feature of global searching optimal solution of genetic algorithms, this algorithm can optimize the cooperative multi-task assignment of UAVs cluster. Simulation shows that the proposed algorithm can achieve more optimized solution of cooperative multi-task assignment.
出处
《电子科技大学学报》
EI
CAS
CSCD
北大核心
2013年第5期723-727,共5页
Journal of University of Electronic Science and Technology of China
基金
航空科学基金(2012ZC52042)
关键词
协同作战
遗传算法
多任务
任务分配
无人机群
cooperative combat
genetic algorithms
multi-task
task assignment
unmanned aerial vehicles cluster
