Article
Journal :
International Journal of Reasoning-based Intelligent Systems (IJRIS)
ISSN : 1755-0564
Publisher :
Information
Year : 2017
Volume : 9 Number : 1
Pages : 22-42
Details
A 0-1 bat algorithm for cellular network optimisation: a systematic study on mapping techniques
Many research efforts are deployed today in order to design techniques that allow continuous metaheuristics to also solve binary problems. However, knowing that no work thoroughly studied these techniques, such a task is still difficult since these techniques are still ambiguous and misunderstood. The bat algorithm (BA) is a continuous algorithm that has been recently adapted using one of these techniques. However, that work suffered from several shortfalls. This paper conducts a systematic study in order to investigate the efficiency and usefulness of discretising continuous metaheuristics. This is done by proposing five binary variants of the BA (BBAs) based on the principal mapping techniques existing in the literature. As problem benchmark, two optimisation problems in cellular networks, the antenna positioning problem (APP) and the reporting cell problem (RCP) are used. The proposed BBAs are evaluated using several types, sizes and complexities of data. Two of the top-ranked algorithms designed to solve the APP and the RCP, the population-based incremental learning (PBIL) and the differential evolution (DE) algorithm are taken as comparison basis. Several statistical tests are conducted as well.
Key words :
Bat algorithm Binary problems Mapping techniques Antenna positioning problem APP Reporting cell problem RCP
Ref. citation :
misc-lab-67
DOI :
10.1504/IJRIS.2017.10007147
Link :
Texte intégral
ACM :
Z. A. Dahi, C. Mezioud and A. Draa. 2017. A 0-1 bat algorithm for cellular network optimisation: a systematic study on mapping techniques. International Journal of Reasoning-based Intelligent Systems (IJRIS), 9, 1, Inderscience, 22-42. DOI: https://doi.org/10.1504/IJRIS.2017.10007147.
APA :
Dahi, Z. A., Mezioud, C. & Draa, A. (2017). A 0-1 bat algorithm for cellular network optimisation: a systematic study on mapping techniques. International Journal of Reasoning-based Intelligent Systems (IJRIS), 9(1), Inderscience, 22-42. DOI: https://doi.org/10.1504/IJRIS.2017.10007147
IEEE :
Z. A. Dahi, C. Mezioud and A. Draa, "A 0-1 bat algorithm for cellular network optimisation: a systematic study on mapping techniques". International Journal of Reasoning-based Intelligent Systems (IJRIS), vol. 9, no. 1, Inderscience, pp. 22-42, 2017. DOI: https://doi.org/10.1504/IJRIS.2017.10007147.
BibTeX :
@article{misc-lab-67,
author = {Dahi, Zakaria Abdelmoiz and Mezioud, Chaker and Draa, Amer},
title = {A 0-1 bat algorithm for cellular network optimisation: a systematic study on mapping techniques},
journal = {International Journal of Reasoning-based Intelligent Systems (IJRIS)},
volume = {9},
number = {1},
issn = {1755-0564},
pages = {22--42},
publisher = {Inderscience},
year = {2017},
doi = {10.1504/IJRIS.2017.10007147},
url = {https://www.inderscienceonline.com/doi/abs/10.1504/IJRIS.2017.086149},
keywords = {Bat algorithm, binary problems, mapping techniques, antenna positioning problem, APP, reporting cell problem, RCP}
}
RIS :
TI  - A 0-1 bat algorithm for cellular network optimisation: a systematic study on mapping techniques
AU - Z. A. Dahi
AU - C. Mezioud
AU - A. Draa
PY - 2017
SN - 1755-0564
JO - International Journal of Reasoning-based Intelligent Systems (IJRIS)
VL - 9
IS - 1
SP - 22
EP - 42
PB - Inderscience
AB - Many research efforts are deployed today in order to design techniques that allow continuous metaheuristics to also solve binary problems. However, knowing that no work thoroughly studied these techniques, such a task is still difficult since these techniques are still ambiguous and misunderstood. The bat algorithm (BA) is a continuous algorithm that has been recently adapted using one of these techniques. However, that work suffered from several shortfalls. This paper conducts a systematic study in order to investigate the efficiency and usefulness of discretising continuous metaheuristics. This is done by proposing five binary variants of the BA (BBAs) based on the principal mapping techniques existing in the literature. As problem benchmark, two optimisation problems in cellular networks, the antenna positioning problem (APP) and the reporting cell problem (RCP) are used. The proposed BBAs are evaluated using several types, sizes and complexities of data. Two of the top-ranked algorithms designed to solve the APP and the RCP, the population-based incremental learning (PBIL) and the differential evolution (DE) algorithm are taken as comparison basis. Several statistical tests are conducted as well.
KW - Bat algorithm
KW - binary problems
KW - mapping techniques
KW - antenna positioning problem
KW - APP
KW - reporting cell problem
KW - RCP
DO - 10.1504/IJRIS.2017.10007147
UR - https://www.inderscienceonline.com/doi/abs/10.1504/IJRIS.2017.086149
ID - misc-lab-67
ER -