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A hyper-heuristic based on random gradient, greedy and dominance

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A hyper-heuristic based on random gradient, greedy and dominance. / Özcan, Ender; Kheiri, Ahmed.
Computer and Information Sciences II: 26th International Symposium on Computer and Information Sciences. ed. / Erol Gelenbe; Ricardo Lent; Georgia Sakellari. Vol. 2 Springer, 2012. p. 557-563.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Harvard

Özcan, E & Kheiri, A 2012, A hyper-heuristic based on random gradient, greedy and dominance. in E Gelenbe, R Lent & G Sakellari (eds), Computer and Information Sciences II: 26th International Symposium on Computer and Information Sciences. vol. 2, Springer, pp. 557-563, 26th Annual International Symposium on Computer and Information Science, ISCIS 2011, London, United Kingdom, 26/09/11. https://doi.org/10.1007/978-1-4471-2155-8_71

APA

Özcan, E., & Kheiri, A. (2012). A hyper-heuristic based on random gradient, greedy and dominance. In E. Gelenbe, R. Lent, & G. Sakellari (Eds.), Computer and Information Sciences II: 26th International Symposium on Computer and Information Sciences (Vol. 2, pp. 557-563). Springer. https://doi.org/10.1007/978-1-4471-2155-8_71

Vancouver

Özcan E, Kheiri A. A hyper-heuristic based on random gradient, greedy and dominance. In Gelenbe E, Lent R, Sakellari G, editors, Computer and Information Sciences II: 26th International Symposium on Computer and Information Sciences. Vol. 2. Springer. 2012. p. 557-563 doi: 10.1007/978-1-4471-2155-8_71

Author

Özcan, Ender ; Kheiri, Ahmed. / A hyper-heuristic based on random gradient, greedy and dominance. Computer and Information Sciences II: 26th International Symposium on Computer and Information Sciences. editor / Erol Gelenbe ; Ricardo Lent ; Georgia Sakellari. Vol. 2 Springer, 2012. pp. 557-563

Bibtex

@inproceedings{b94d181a12b744d99c926b626b8a7b88,
title = "A hyper-heuristic based on random gradient, greedy and dominance",
abstract = "Hyper-heuristics have emerged as effective general methodologies that are motivated by the goal of building or selecting heuristics automatically to solve a range of hard computational search problems with less development cost. HyFlex is a publicly available hyper-heuristic tool for rapid development and research which currently provides an interface to four problem domains along with relevant low level heuristics. A multistage hyper-heuristic based on random gradient and greedy with dominance heuristic selection methods is introduced in this study. This hyper-heuristic is implemented as an extension to HyFlex. The empirical results show that our approach performs better than some previously proposed hyper-heuristics over the given problem domains.",
author = "Ender {\"O}zcan and Ahmed Kheiri",
year = "2012",
month = dec,
day = "1",
doi = "10.1007/978-1-4471-2155-8_71",
language = "English",
isbn = "9781447121541",
volume = "2",
pages = "557--563",
editor = "Erol Gelenbe and Ricardo Lent and Georgia Sakellari",
booktitle = "Computer and Information Sciences II",
publisher = "Springer",
note = "26th Annual International Symposium on Computer and Information Science, ISCIS 2011 ; Conference date: 26-09-2011 Through 28-09-2011",

}

RIS

TY - GEN

T1 - A hyper-heuristic based on random gradient, greedy and dominance

AU - Özcan, Ender

AU - Kheiri, Ahmed

PY - 2012/12/1

Y1 - 2012/12/1

N2 - Hyper-heuristics have emerged as effective general methodologies that are motivated by the goal of building or selecting heuristics automatically to solve a range of hard computational search problems with less development cost. HyFlex is a publicly available hyper-heuristic tool for rapid development and research which currently provides an interface to four problem domains along with relevant low level heuristics. A multistage hyper-heuristic based on random gradient and greedy with dominance heuristic selection methods is introduced in this study. This hyper-heuristic is implemented as an extension to HyFlex. The empirical results show that our approach performs better than some previously proposed hyper-heuristics over the given problem domains.

AB - Hyper-heuristics have emerged as effective general methodologies that are motivated by the goal of building or selecting heuristics automatically to solve a range of hard computational search problems with less development cost. HyFlex is a publicly available hyper-heuristic tool for rapid development and research which currently provides an interface to four problem domains along with relevant low level heuristics. A multistage hyper-heuristic based on random gradient and greedy with dominance heuristic selection methods is introduced in this study. This hyper-heuristic is implemented as an extension to HyFlex. The empirical results show that our approach performs better than some previously proposed hyper-heuristics over the given problem domains.

U2 - 10.1007/978-1-4471-2155-8_71

DO - 10.1007/978-1-4471-2155-8_71

M3 - Conference contribution/Paper

AN - SCOPUS:84875097299

SN - 9781447121541

VL - 2

SP - 557

EP - 563

BT - Computer and Information Sciences II

A2 - Gelenbe, Erol

A2 - Lent, Ricardo

A2 - Sakellari, Georgia

PB - Springer

T2 - 26th Annual International Symposium on Computer and Information Science, ISCIS 2011

Y2 - 26 September 2011 through 28 September 2011

ER -