摘要
异构型无人机(UAV)群体任务分配机制起着至关重要的作用,分析了并行任务分配的特点,以时间消耗最短为优化目标,建立了整数线性规划的任务优化分配模型。对基本遗传算法进行了改进,提出了有效降低算法复杂度的编码方案,建立了相应的适应度函数,改进了现有遗传算法的变异策略。仿真案例表明该算法具有较强的寻优能力,能够有效地完成异构型群体UAV的并行任务分配。
The task allocation mechanism for a group of heterogeneous unmanned aerial vehicles(UAVs)plays a vital role for mission accomplishment.The characteristics of parallel task allocation was analyzed.With the optimization objective of minimizing the total mission execution time,the integer linear programming model for optimal allocation of tasks was formulated.A new algorithm based on genetic algorithm(GA)for solving such a problem was proposed,based on which the new coding scheme was proposed to reduce the computational complexity effectively,fitness function was established,and mutation strategy was improved,etc.Simulation scenarios show that the algorithm has achieved the optimal allocation of tasks.Result cab verify the effectiveness of the proposed model and algorithm.
作者
宋育武
贾林通
李娟
郭浩
SONG Yue-wu;JIA Lin-tong;LI Juan;GUO Hao(Theory Training Department of Harbin Air Force Flight Academy,Harbin 150001,China;Science and Technology on Underwater Vehicle Technology,Harbin 150001,China;College of Auotmation,Harbin Engineering University,Harbin 150001,China)
出处
《科学技术与工程》
北大核心
2020年第4期1492-1497,共6页
Science Technology and Engineering
基金
国家自然科学基金(51609046)
水下机器人重点实验室研究基金(614221502061701)。
关键词
无人机群体
并行任务分配
遗传算法
整数线性规划
unmanned aerial vehicles
parallel task allocation
genetic algorithm
integer linear programming
