Standard
Performance of selection hyper-heuristics on the extended hyflex domains. / Almutairi, Alhanof; Özcan, Ender; Kheiri, Ahmed et al.
Computer and Information Sciences - 31st International Symposium, ISCIS 2016, Proceedings. ed. / Ricardo Lent; Erol Gelenbe; Tadeusz Czachórski; Krzysztof Grochla. Springer Verlag, 2016. p. 154-162 (Communications in Computer and Information Science; Vol. 659).
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Harvard
Almutairi, A, Özcan, E, Kheiri, A & Jackson, WG 2016,
Performance of selection hyper-heuristics on the extended hyflex domains. in R Lent, E Gelenbe, T Czachórski & K Grochla (eds),
Computer and Information Sciences - 31st International Symposium, ISCIS 2016, Proceedings. Communications in Computer and Information Science, vol. 659, Springer Verlag, pp. 154-162, 31st International Symposium on Computer and Information Sciences, ISCIS 2016, Kraków, Poland,
27/10/16.
https://doi.org/10.1007/978-3-319-47217-1_17APA
Almutairi, A., Özcan, E., Kheiri, A., & Jackson, W. G. (2016).
Performance of selection hyper-heuristics on the extended hyflex domains. In R. Lent, E. Gelenbe, T. Czachórski, & K. Grochla (Eds.),
Computer and Information Sciences - 31st International Symposium, ISCIS 2016, Proceedings (pp. 154-162). (Communications in Computer and Information Science; Vol. 659). Springer Verlag.
https://doi.org/10.1007/978-3-319-47217-1_17Vancouver
Almutairi A, Özcan E, Kheiri A, Jackson WG.
Performance of selection hyper-heuristics on the extended hyflex domains. In Lent R, Gelenbe E, Czachórski T, Grochla K, editors, Computer and Information Sciences - 31st International Symposium, ISCIS 2016, Proceedings. Springer Verlag. 2016. p. 154-162. (Communications in Computer and Information Science). doi: 10.1007/978-3-319-47217-1_17
Author
Almutairi, Alhanof ; Özcan, Ender ; Kheiri, Ahmed et al. /
Performance of selection hyper-heuristics on the extended hyflex domains. Computer and Information Sciences - 31st International Symposium, ISCIS 2016, Proceedings. editor / Ricardo Lent ; Erol Gelenbe ; Tadeusz Czachórski ; Krzysztof Grochla. Springer Verlag, 2016. pp. 154-162 (Communications in Computer and Information Science).
Bibtex
@inproceedings{e4c54afe96a54ed9ae1f7e38064c9d32,
title = "Performance of selection hyper-heuristics on the extended hyflex domains",
abstract = "Selection hyper-heuristics perform search over the space of heuristics by mixing and controlling a predefined set of low level heuristics for solving computationally hard combinatorial optimisation problems. Being reusable methods, they are expected to be applicable to multiple problem domains, hence performing well in cross-domain search. HyFlex is a general purpose heuristic search API which separates the high level search control from the domain details enabling rapid development and performance comparison of heuristic search methods, particularly hyper-heuristics. In this study, the performance of six previously proposed selection hyper-heuristics are evaluated on three recently introduced extended HyFlex problem domains, namely 0-1 Knapsack, Quadratic Assignment and Max-Cut. The empirical results indicate the strong generalising capability of two adaptive selection hyper-heuristics which perform well across the {\textquoteleft}unseen{\textquoteright} problems in addition to the six standard HyFlex problem domains.",
keywords = "Adaptation, Metaheuristic, Move acceptance, Optimisation, Parameter control",
author = "Alhanof Almutairi and Ender {\"O}zcan and Ahmed Kheiri and Jackson, {Warren G.}",
year = "2016",
month = sep,
day = "24",
doi = "10.1007/978-3-319-47217-1_17",
language = "English",
isbn = "9783319472164",
series = "Communications in Computer and Information Science",
publisher = "Springer Verlag",
pages = "154--162",
editor = "Ricardo Lent and Erol Gelenbe and Tadeusz Czach{\'o}rski and Krzysztof Grochla",
booktitle = "Computer and Information Sciences - 31st International Symposium, ISCIS 2016, Proceedings",
address = "Germany",
note = "31st International Symposium on Computer and Information Sciences, ISCIS 2016 ; Conference date: 27-10-2016 Through 28-10-2016",
}
RIS
TY - GEN
T1 - Performance of selection hyper-heuristics on the extended hyflex domains
AU - Almutairi, Alhanof
AU - Özcan, Ender
AU - Kheiri, Ahmed
AU - Jackson, Warren G.
PY - 2016/9/24
Y1 - 2016/9/24
N2 - Selection hyper-heuristics perform search over the space of heuristics by mixing and controlling a predefined set of low level heuristics for solving computationally hard combinatorial optimisation problems. Being reusable methods, they are expected to be applicable to multiple problem domains, hence performing well in cross-domain search. HyFlex is a general purpose heuristic search API which separates the high level search control from the domain details enabling rapid development and performance comparison of heuristic search methods, particularly hyper-heuristics. In this study, the performance of six previously proposed selection hyper-heuristics are evaluated on three recently introduced extended HyFlex problem domains, namely 0-1 Knapsack, Quadratic Assignment and Max-Cut. The empirical results indicate the strong generalising capability of two adaptive selection hyper-heuristics which perform well across the ‘unseen’ problems in addition to the six standard HyFlex problem domains.
AB - Selection hyper-heuristics perform search over the space of heuristics by mixing and controlling a predefined set of low level heuristics for solving computationally hard combinatorial optimisation problems. Being reusable methods, they are expected to be applicable to multiple problem domains, hence performing well in cross-domain search. HyFlex is a general purpose heuristic search API which separates the high level search control from the domain details enabling rapid development and performance comparison of heuristic search methods, particularly hyper-heuristics. In this study, the performance of six previously proposed selection hyper-heuristics are evaluated on three recently introduced extended HyFlex problem domains, namely 0-1 Knapsack, Quadratic Assignment and Max-Cut. The empirical results indicate the strong generalising capability of two adaptive selection hyper-heuristics which perform well across the ‘unseen’ problems in addition to the six standard HyFlex problem domains.
KW - Adaptation
KW - Metaheuristic
KW - Move acceptance
KW - Optimisation
KW - Parameter control
U2 - 10.1007/978-3-319-47217-1_17
DO - 10.1007/978-3-319-47217-1_17
M3 - Conference contribution/Paper
AN - SCOPUS:84989345061
SN - 9783319472164
T3 - Communications in Computer and Information Science
SP - 154
EP - 162
BT - Computer and Information Sciences - 31st International Symposium, ISCIS 2016, Proceedings
A2 - Lent, Ricardo
A2 - Gelenbe, Erol
A2 - Czachórski, Tadeusz
A2 - Grochla, Krzysztof
PB - Springer Verlag
T2 - 31st International Symposium on Computer and Information Sciences, ISCIS 2016
Y2 - 27 October 2016 through 28 October 2016
ER -
