[1]施展 ,陈庆伟.基于改进的多目标量子行为粒子群优化算法的多无人机协同任务分配[J].南京理工大学学报(自然科学版),2012,36(06):0.
 SHI Zhan,CHEN Qing wei.Cooperative Task Allocation for Multiple UAVs Based on Improved Multiobjective Quantumbehaved Particle Swarm Optimization Algorithm[J].Journal of Nanjing University of Science and Technology,2012,36(06):0.
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基于改进的多目标量子行为粒子群优化算法的多无人机协同任务分配
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《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
36卷
期数:
2012年06期
页码:
0
栏目:
出版日期:
2012-12-31

文章信息/Info

Title:
Cooperative Task Allocation for Multiple UAVs Based on Improved Multiobjective Quantumbehaved Particle Swarm Optimization Algorithm
作者:
施展 12陈庆伟 1
1.南京理工大学 自动化学院,江苏 南京 210094;2.中国电子科技集团公司 第二十八研究所,江苏 南京 210007
Author(s):
SHI Zhan12CHEN Qingwei1
1.School of Automation,NUST,Nanjing 210094,China; 2.28th Research Institute of China Electronics Technology Group Corporation,Nanjing 210007,China
关键词:
多无人机多目标优化量子行为粒子群优化任务分配自主选择
Keywords:
multiple unmanned aerial vehiclesmultiobjective optimizationquantumbehaved particle swarm optimizationtask allocationautonomous selection
分类号:
TP391;V279
摘要:
为在给定的时间内以最小代价和最大效益完成任务,建立了多无人机协同任务分配问题的多目标优化模型。采用改进的多目标量子行为粒子群优化算法求解最优任务分配方案,定义了一种从所求候选方案中选取最优分配方案的自主选择准则。对比分析多目标粒子群优化、多目标进化算法和该文算法所求的最优分配方案。仿真结果表明该文算法能够较快地求解问题,而且所求最优任务分配方案的性能优于其它三种算法。
Abstract:
To accomplish ordered missions with the least cost and most benefit in given time,a multiobjective optimization model for cooperative task allocation of multiple unmanned aerial vehicles(UAVs)is established.An improved multiobjective quantumbehaved particle swarm optimization algorithm is used to solve the optimal task allocation scheme.An autonomous selection criterion for optimal allocation scheme choice in the obtained optional schemes is defined.The optimal allocation schemes solved by the multiobjective particle swarm optimization,the multiobjective evolutionary algorithm and the algorithm in this paper are contrastly analyzed.The simulation results show the proposed approach can solute the problem fast,and the performance of the task allocation scheme of this approach is better than others.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2011-05-18修回日期:2012-10-16 基金项目:国家自然科学基金(60975075;61074023);总装“十二五”预先研究项目;江苏省自然科学基金(BK2008404) 作者简介:施展(1984-),男,博士,工程师,主要研究方向:智能控制、多目标优化理论与算法,Email:z_shi2006@163.com;通讯作者:陈庆伟(1963-),男,教授,博士生导师,主要研究方向:智能控制、网络控制系统和高精度数字伺服系统等,Email:cqw1002@njust.edu.cn。
更新日期/Last Update: 2012-12-29