A Multi-Objective Hyper-Heuristic for Unmanned Aerial Vehicle Data Collection in Wireless Sensor Networks

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@InProceedings{Huang:2019:SSCI,

• author = "Zhixing Huang and Chengyu Lu and Jinghui Zhong",
• booktitle = "2019 IEEE Symposium Series on Computational Intelligence (SSCI)",
• title = "A Multi-Objective Hyper-Heuristic for Unmanned Aerial Vehicle Data Collection in Wireless Sensor Networks",
• year = "2019",
• pages = "1614--1621",
• abstract = "Monitoring dangerous regions is one of the most important applications of wireless sensor networks. Limited by the danger of monitoring regions and the battery power of sensors, unmanned aerial vehicles (UAVs) are often used to collect data in such applications. How to properly schedule the movement of UAVs to efficiently collect data is still a challenging problem to be solved. In this paper, we formulate the UAV scheduling problem as a multi-objective optimization problem and design a genetic programming based hyper-heuristic framework to solve the problem. The simulation results show that our method can provide very promising performance in comparison with several state-of-the-art methods.",
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1109/SSCI44817.2019.9002862",
• month = dec,
• notes = "Also known as \cite{9002862}",

}

Genetic Programming entries for Zhixing Huang Chengyu Lu Jinghui Zhong

Citations