无人机集群任务分配的多目标算法研究  

Research on the multi-objective algorithm of UAV cluster task allocation

作　　者：高卫峰 王琼 李宏 谢晋 公茂果[2] GAO Weifeng;WANG Qiong;LI Hong;XIE Jin;GONG Maoguo(School of Mathematics and Statistics,Xidian University,Xi’an 710071,China;Key Laboratory of Collaborative Intelligent Systems,Ministry of Education,Xidian University,Xi’an 710071,China)

机构地区：[1]西安电子科技大学数学与统计学院,陕西西安710071 [2]西安电子科技大学协同智能系统教育部重点实验室,陕西西安710071

出　　处：《西安电子科技大学学报》2024年第2期1-12,共12页Journal of Xidian University

基　　金：国家自然科学基金(62276202,62106186)。

摘　　要：针对目标识别场景下的无人机集群协同任务分配问题,建立了以识别代价和识别收益为目标的优化模型,设计了基于分解的多目标差分进化算法求解该模型。首先,提出了精英初始化方法,在保证所得非支配解分布均匀的基础上,筛选初始解以提高解集的质量;其次,结合模型特性构造整数编码下的多目标差分进化算子,提高算法的收敛速度;最后,设计了带限制的禁忌搜索策略,使得算法具有跳出局部最优的能力。该算法为问题的求解提供一组非支配解集,使得可以根据实际需求选择更加合理的最优解。通过上述方法获得分配方案后,基于拍卖算法设计任务重分配策略,进一步调整分配方案,以应对无人机损毁的突发情况。仿真实验验证了所提算法在求解小、中、大规模任务分配问题上的有效性。相比于其他算法,文中算法所得非支配集具有更高的质量,可以消耗更少的识别代价来获取更高的识别收益,说明算法具有一定的优越性。Aiming at the cooperative task allocation problem of UAV swarm in target recognition scenario,an optimization model with recognition cost and recognition benefit as the goal is established,and a multi-objective differential evolution algorithm based on decomposition is designed to solve the model.First,an elite initialization method is proposed,and the initial solution is screened to improve the quality of the solution set on the basis of ensuring the uniform distribution of the obtained nondominated solution.Second,the multi-objective differential evolution operator under integer encoding is constructed based on the model characteristics to improve the convergence speed of the algorithm.Finally,a tabul search strategy with restrictions is designed,so that the algorithm has the ability to jump out of the local optimal.The algorithm provides a set of nondominated solution sets for the solution of the problem,so that a more reasonable optimal solution can be selected according to actual needs.After obtaining the allocation scheme by the above method,the task reallocation strategy is designed based on the auction algorithm,and the allocation scheme is further adjusted to cope with the unexpected situation of UAV damage.On the one hand,simulation experiments verify the effectiveness of the proposed algorithm in solving small,medium and large-scale task allocation problems,and on the other hand,compared with other algorithms,the nondominated set obtained by the proposed algorithm has a higher quality,which can consume less recognition cost and obtain higher recognition revenue,indicating that the proposed algorithm has certain advantages.

关 键 词：任务分配 无人机 多目标算法 进化算法 禁忌搜索 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]