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Dahi, Zakaria Abdelmoiz Alba-Torres, Enrique 2022-04-19T12:24:01Z 2022-04-19T12:24:01Z 2022-02 Zakaria Abdelmoiz, Dahi ; Alba-Torres, Enrique ; Luque-Polo, Gabriel Jesús. A takeover time-driven adaptive evolutionary algorithm for mobile user tracking in pre-5G cellular networks. Applied Soft Computing Volume 116, February 2022, 107992. https://doi.org/10.1016/j.asoc.2021.107992 https://hdl.handle.net/10630/23945 10.1016/j.asoc.2021.107992 Cellular networks are one of today’s most popular means of communication. This fact has made the mobile phone industry subject to a huge scientific and economic competition, where the quality of service is key. Such a quality is measured on the basis of reliability, speed and accuracy when delivering a service to a user no matter his location or behaviour are. This fact has placed the users’ tracking process among the most difficult and determining issues in cellular network design. In this paper, we present an adaptive bi-phased evolutionary algorithm based on the takeover time to solve this problem. The proposal is thoroughly assessed by tackling twenty-five real-world instances of different sizes. Twenty-eight of the state-of-the-art techniques devised to address the users’ mobility problem have been taken as the comparison basis, and several statistical tests have been also conducted. Experiments have demonstrated that our solver outperforms most of the top-ranked algorithms. eng http://creativecommons.org/licenses/by-nc-nd/4.0/ open access Attribution-NonCommercial-NoDerivatives 4.0 Internacional Comunicación -- Análisis de red A takeover time-driven adaptive evolutionary algorithm for mobile user tracking in pre-5G cellular networks journal article