@inproceedings{9b737c370fe241238db7ab2e9109a907,
title = "Multi-level grammar genetic programming for scheduling in heterogeneous networks",
abstract = "Co-ordination of Inter-Cell Interference through scheduling enables telecommunication companies to better exploit their Heterogeneous Networks. However, it requires from these entities to implement an effective scheduling algorithm. The state-of-the-art for the scheduling in Heterogeneous Networks is a Grammar-Guided Genetic Programming algorithm which evolves, from a given grammar, an expression that maps to the scheduling of transmissions. We evaluate in our work the possibility of improving the results obtained by the state-of-the-art using a layered grammar approach. We show that starting with a small restricted grammar and introducing the full functionality after 10 generations outperforms the state-of-the-art, even when varying the algorithm used to generate the initial population and the maximum initial tree depth.",
keywords = "Grammar-guided genetic programming, Heterogeneous network, Multi-level grammar, Scheduling, Telecommunication",
author = "Takfarinas Saber and David Fagan and David Lynch and Stepan Kucera and Holger Claussen and Michael O{\textquoteright}Neill",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG, part of Springer Nature 2018.; 21st European Conference on Genetic Programming, EuroGP 2018 ; Conference date: 04-04-2018 Through 06-04-2018",
year = "2018",
doi = "10.1007/978-3-319-77553-1\_8",
language = "English",
isbn = "9783319775524",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "118--134",
editor = "Stefano Cagnoni and Mengjie Zhang and Pablo Garcia-Sanchez and Mauro Castelli and Lukas Sekanina",
booktitle = "Genetic Programming - 21st European Conference, EuroGP 2018, Proceedings",
address = "Germany",
}