UAV search-and-rescue planning using an adaptive memetic algorithm
Author:
Publisher
Zhejiang University Press
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing
Link
https://link.springer.com/content/pdf/10.1631/FITEE.2000632.pdf
Reference57 articles.
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4. Bourgault F, Furukawa T, Durrant-Whyte HF, 2006. Optimal search for a lost target in a Bayesian world. In: Yuta S, Asama H, Prassler E, et al. (Eds.), Field and Service Robotics: Recent Advances in Research and Applications. Springer, Berlin, Heidelberg, p.209–222. https://doi.org/10.1007/10991459_21
5. Burcin Ozsoydan F, Sağir M, 2021. Iterated greedy algorithms enhanced by hyper-heuristic based learning for hybrid flexible flowshop scheduling problem with sequence dependent setup times: a case study at a manufacturing plant. Comput Oper Res, 125:105044. https://doi.org/10.1016/j.cor.2020.105044
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