Optimization of Pesticide Spraying Tasks via Multi-UAVs Using Genetic Algorithm
Joint Authors
Hu, Xiaoxuan
Luo, He
Niu, Yanqiu
Zhu, Moning
Ma, Huawei
Source
Mathematical Problems in Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-11-12
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Abstract EN
Task allocation is the key factor in the spraying pesticides process using unmanned aerial vehicles (UAVs), and maximizing the effects of pesticide spraying is the goal of optimizing UAV pesticide spraying.
In this study, we first introduce each UAV’s kinematic constraint and extend the Euclidean distance between fields to the Dubins path distance.
We then analyze the two factors affecting the pesticide spraying effects, which are the type of pesticides and the temperature during the pesticide spraying.
The time window of the pesticide spraying is dynamically generated according to the temperature and is introduced to the pesticide spraying efficacy function.
Finally, according to the extensions, we propose a team orienteering problem with variable time windows and variable profits model.
We propose the genetic algorithm to solve the above model and give the methods of encoding, crossover, and mutation in the algorithm.
The experimental results show that this model and its solution method have clear advantages over the common manual allocation strategy and can provide the same results as those of the enumeration method in small-scale scenarios.
In addition, the results also show that the algorithm parameter can affect the solution, and we provide the optimal parameters configuration for the algorithm.
American Psychological Association (APA)
Luo, He& Niu, Yanqiu& Zhu, Moning& Hu, Xiaoxuan& Ma, Huawei. 2017. Optimization of Pesticide Spraying Tasks via Multi-UAVs Using Genetic Algorithm. Mathematical Problems in Engineering،Vol. 2017, no. 2017, pp.1-16.
https://search.emarefa.net/detail/BIM-1191673
Modern Language Association (MLA)
Niu, Yanqiu…[et al.]. Optimization of Pesticide Spraying Tasks via Multi-UAVs Using Genetic Algorithm. Mathematical Problems in Engineering No. 2017 (2017), pp.1-16.
https://search.emarefa.net/detail/BIM-1191673
American Medical Association (AMA)
Luo, He& Niu, Yanqiu& Zhu, Moning& Hu, Xiaoxuan& Ma, Huawei. Optimization of Pesticide Spraying Tasks via Multi-UAVs Using Genetic Algorithm. Mathematical Problems in Engineering. 2017. Vol. 2017, no. 2017, pp.1-16.
https://search.emarefa.net/detail/BIM-1191673
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1191673