Research on uncertain bi-objective UAV mission allocation problem

被引:0
|
作者
Lisheng Zhang
Mingfa Zheng
Haitao Zhong
Aoyu Zheng
机构
[1] Air Force Engineering University,Fundamentals Department
来源
Evolutionary Intelligence | 2024年 / 17卷
关键词
Uncertainty theory; Bi-objective optimization; UAV mission allocation; Ant colony algorithm;
D O I
暂无
中图分类号
学科分类号
摘要
Based on the uncertainty theory, this paper studies the uncertain bi-objective UAV mission allocation problem in uncertain environment. Firstly, by regarding uncertainty factors in the mission allocation planning as uncertain variables and considering two missions of combat mission gains and flight fuel consumption, a uncertain bi-objective UAV mission allocation (UBUMA) model is established. Secondly, in order to overcome the disconnection between the objective functions caused by the traditional method to deal with uncertain factors, this paper proposes a so-called uncertain method to solve UBMUA problem by defining the relationship of order between uncertain variables. According the real decision-making process, the UBUMA is transformed into a single-objective programming problem by using CE\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$C_E$$\end{document} principle relation. Finally, the ant algorithm is employed to solve the single-objective programming problem and then the CE\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$C_E$$\end{document} efficient mission routes are obtained. The simulation results show that this method can effectively deal with UBUMA problem, and the mission allocation efficient routes is reasonable.
引用
收藏
页码:229 / 237
页数:8
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