Many-objective task allocation method based on D-NSGA-III algorithm for multi-UAVs

被引：1
|
作者：
Zhou J. [1 ,2 ]
Zhao X. [1 ]
Xu Z. [3 ]
Lin Z. [2 ]
Zhang X. [3 ]
机构：
[1] School of Management and Economics, Dalian University of Technology, Dalian
[2] Institute of Operation Software and Simulation, Dalian Naval Academy, Dalian
[3] School of Computer Science and Technology, Wuhan University of Technology, Wuhan
来源：
Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics | 2021年 / 43卷 / 05期
关键词：
Distributed evolutionary algorithm; Many-objective optimization algorithm; Migration strategy; Task allocation;
D O I：
10.12305/j.issn.1001-506X.2021.05.11
中图分类号：
TU [建筑科学];
学科分类号：
0813 ;
摘要：
With the rapid development of artificial intelligence technology, a variety of unmanned aerial vehicles (UAVs) have been widely used in the military field. Due to the limitation of resource allocation and executive capability of single platform, most of complex tasks should be accomplished by the cooperation of multiple UAVs. Optimal task allocation is one of the critical and difficult problems to be solved, and it has been proven to be an NP-hard problem. Considering the organization architecture of multi-UAVs system, the non-dominated genetic algorithm is combined with island model and master-slave model. A distributed many-objective evolutionary algorithm, named D-NAGA-III, is built to optimize four objects in a real application, and a migration strategy and greedy algorithm are proposed to improve the optimization ability and enhance the solution quality. Experimental results show that the proposed method is effective in solving distributed many-objective task allocation problems in UAVs systems. © 2021, Editorial Office of Systems Engineering and Electronics. All right reserved.
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页码：1240 / 1247
页数：7
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