By the same authors

Templar – A Framework for Template-Method Hyper-Heuristics

Research output: Chapter in Book/Report/Conference proceeding › Chapter (peer-reviewed) › peer-review

Standard

Templar – A Framework for Template-Method Hyper-Heuristics. / Swan, Jeremiah; Burles, Nathan John.

Genetic Programming: 18th European Conference, EuroGP 2015, Copenhagen, Denmark, April 8-10, 2015, Proceedings. ed. / Penousal Machado; Malcolm Heywood; James McDermott; Mauro Castelli; Pablo Garcia-Sanchez; Paolo Burelli; Sebastian Risi; Kevin Sim. Cham : Springer International Publishing, 2015. p. 205-216 (Lecture Notes in Computer Science; Vol. 9025).

Research output: Chapter in Book/Report/Conference proceeding › Chapter (peer-reviewed) › peer-review

Harvard

Swan, J & Burles, NJ 2015, Templar – A Framework for Template-Method Hyper-Heuristics. in P Machado, M Heywood, J McDermott, M Castelli, P Garcia-Sanchez, P Burelli, S Risi & K Sim (eds), Genetic Programming: 18th European Conference, EuroGP 2015, Copenhagen, Denmark, April 8-10, 2015, Proceedings. Lecture Notes in Computer Science, vol. 9025, Springer International Publishing, Cham, pp. 205-216, European Conference on Genetic Programming, EuroGP 2015, Copenhagen, Denmark, 8/04/15. https://doi.org/10.1007/978-3-319-16501-1_17

APA

Swan, J., & Burles, N. J. (2015). Templar – A Framework for Template-Method Hyper-Heuristics. In P. Machado, M. Heywood, J. McDermott, M. Castelli, P. Garcia-Sanchez, P. Burelli, S. Risi, & K. Sim (Eds.), Genetic Programming: 18th European Conference, EuroGP 2015, Copenhagen, Denmark, April 8-10, 2015, Proceedings (pp. 205-216). (Lecture Notes in Computer Science; Vol. 9025). Springer International Publishing. https://doi.org/10.1007/978-3-319-16501-1_17

Vancouver

Swan J, Burles NJ. Templar – A Framework for Template-Method Hyper-Heuristics. In Machado P, Heywood M, McDermott J, Castelli M, Garcia-Sanchez P, Burelli P, Risi S, Sim K, editors, Genetic Programming: 18th European Conference, EuroGP 2015, Copenhagen, Denmark, April 8-10, 2015, Proceedings. Cham: Springer International Publishing. 2015. p. 205-216. (Lecture Notes in Computer Science). https://doi.org/10.1007/978-3-319-16501-1_17

Author

Swan, Jeremiah ; Burles, Nathan John. / Templar – A Framework for Template-Method Hyper-Heuristics. Genetic Programming: 18th European Conference, EuroGP 2015, Copenhagen, Denmark, April 8-10, 2015, Proceedings. editor / Penousal Machado ; Malcolm Heywood ; James McDermott ; Mauro Castelli ; Pablo Garcia-Sanchez ; Paolo Burelli ; Sebastian Risi ; Kevin Sim. Cham : Springer International Publishing, 2015. pp. 205-216 (Lecture Notes in Computer Science).

Bibtex - Download

@inbook{61af8fa0af494e6da4e3362a41dbf102,
title = "Templar – A Framework for Template-Method Hyper-Heuristics",
abstract = "In this work we introduce Templar, a software framework for customising algorithms via the generative technique of template-method hyper-heuristics. We first discuss the need for such an approach, presenting Quicksort as an example. We provide a functional definition of template-method hyper-heuristics, describe how this is implemented by Templar, and show how Templar may be invoked using simple client-code. Finally, we describe experiments using Templar to define a {\textquoteleft}hyper-quicksort{\textquoteright} with the aim of reducing power consumption—the results demonstrate that the generated algorithm has significantly improved performance on the test set.",
author = "Jeremiah Swan and Burles, {Nathan John}",
year = "2015",
doi = "10.1007/978-3-319-16501-1_17",
language = "English",
isbn = "978-3-319-16500-4",
series = "Lecture Notes in Computer Science",
publisher = "Springer International Publishing",
pages = "205--216",
editor = "Penousal Machado and Malcolm Heywood and James McDermott and Mauro Castelli and Pablo Garcia-Sanchez and Paolo Burelli and Sebastian Risi and Kevin Sim",
booktitle = "Genetic Programming",
note = "European Conference on Genetic Programming, EuroGP 2015 ; Conference date: 08-04-2015 Through 10-04-2015",

}

RIS (suitable for import to EndNote) - Download

TY - CHAP

T1 - Templar – A Framework for Template-Method Hyper-Heuristics

AU - Swan, Jeremiah

AU - Burles, Nathan John

PY - 2015

Y1 - 2015

N2 - In this work we introduce Templar, a software framework for customising algorithms via the generative technique of template-method hyper-heuristics. We first discuss the need for such an approach, presenting Quicksort as an example. We provide a functional definition of template-method hyper-heuristics, describe how this is implemented by Templar, and show how Templar may be invoked using simple client-code. Finally, we describe experiments using Templar to define a ‘hyper-quicksort’ with the aim of reducing power consumption—the results demonstrate that the generated algorithm has significantly improved performance on the test set.

AB - In this work we introduce Templar, a software framework for customising algorithms via the generative technique of template-method hyper-heuristics. We first discuss the need for such an approach, presenting Quicksort as an example. We provide a functional definition of template-method hyper-heuristics, describe how this is implemented by Templar, and show how Templar may be invoked using simple client-code. Finally, we describe experiments using Templar to define a ‘hyper-quicksort’ with the aim of reducing power consumption—the results demonstrate that the generated algorithm has significantly improved performance on the test set.

U2 - 10.1007/978-3-319-16501-1_17

DO - 10.1007/978-3-319-16501-1_17

M3 - Chapter (peer-reviewed)

SN - 978-3-319-16500-4

T3 - Lecture Notes in Computer Science

SP - 205

EP - 216

BT - Genetic Programming

A2 - Machado, Penousal

A2 - Heywood, Malcolm

A2 - McDermott, James

A2 - Castelli, Mauro

A2 - Garcia-Sanchez, Pablo

A2 - Burelli, Paolo

A2 - Risi, Sebastian

A2 - Sim, Kevin

PB - Springer International Publishing

CY - Cham

T2 - European Conference on Genetic Programming, EuroGP 2015

Y2 - 8 April 2015 through 10 April 2015

ER -

York staff: edit these data