@inproceedings{201a1f424cdb40d8a3803a5bf80cb9ec,
title = "Optimal Anti-submarine Search Path for UUV via an Adaptive Mutation Genetic Algorithm",
abstract = "Unmanned underwater vehicle (UUV) is significant equipment for underwater anti-submarine operation. In this paper, the optimal anti-submarine search path for UUV is investigated through an adaptive mutation genetic algorithm (AMGA). The AMGA utilizes three control factors to dominate the direction and amplitude of mutation adaptively and to improve the convergence speed. The mathematical programming model for UUV optimal search is established by maximizing cumulative detection probability (CDP). The enemy submarine is described as Markovian target, and the search radius and search width of the UUV are considered. Reasonable and efficient search paths are obtained under different conditions. The results indicate that the optimal path for UUV is effective and suggestive for anti-submarine search.",
keywords = "Adaptive mutation genetic algorithm (AMGA), Anti-submarine search, Optimal path, Unmanned underwater vehicle (UUV)",
author = "Wenjun Ding and Hui Cao and Hao Wu and Zhaoyong Mao",
note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG.; 12th International Conference on Intelligent Robotics and Applications, ICIRA 2019 ; Conference date: 08-08-2019 Through 11-08-2019",
year = "2019",
doi = "10.1007/978-3-030-27532-7\_42",
language = "英语",
isbn = "9783030275310",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "472--479",
editor = "Haibin Yu and Jinguo Liu and Lianqing Liu and Yuwang Liu and Zhaojie Ju and Dalin Zhou",
booktitle = "Intelligent Robotics and Applications - 12th International Conference, ICIRA 2019, Proceedings",
}