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    Rights statement: © The owners/authors, 2018. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in GECCO '18 Proceedings of the Genetic and Evolutionary Computation Conference Companion (2018) http://doi.acm.org/10.1145/3205651.3208208

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Summary of evolutionary computation for wind farm layout optimization

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

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Summary of evolutionary computation for wind farm layout optimization. / Wilson, Dennis G.; Rodrigues, Silvio; Segura, Carlos et al.
GECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion. Association for Computing Machinery, Inc, 2018. p. 31-32.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Harvard

Wilson, DG, Rodrigues, S, Segura, C, Loshchilov, I, Huer, F, Buenl, GL, Kheiri, A, Keedwell, E, Ocampo-Pineda, M, Özcan, E, Pea, SIV, Goldman, B, Rionda, SB, Hernndez-Aguirre, A, Veeramachaneni, K & Cussat-Blanc, S 2018, Summary of evolutionary computation for wind farm layout optimization. in GECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion. Association for Computing Machinery, Inc, pp. 31-32, 2018 Genetic and Evolutionary Computation Conference, GECCO 2018, Kyoto, Japan, 15/07/18. https://doi.org/10.1145/3205651.3208208

APA

Wilson, D. G., Rodrigues, S., Segura, C., Loshchilov, I., Huer, F., Buenl, G. L., Kheiri, A., Keedwell, E., Ocampo-Pineda, M., Özcan, E., Pea, S. I. V., Goldman, B., Rionda, S. B., Hernndez-Aguirre, A., Veeramachaneni, K., & Cussat-Blanc, S. (2018). Summary of evolutionary computation for wind farm layout optimization. In GECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion (pp. 31-32). Association for Computing Machinery, Inc. https://doi.org/10.1145/3205651.3208208

Vancouver

Wilson DG, Rodrigues S, Segura C, Loshchilov I, Huer F, Buenl GL et al. Summary of evolutionary computation for wind farm layout optimization. In GECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion. Association for Computing Machinery, Inc. 2018. p. 31-32 doi: 10.1145/3205651.3208208

Author

Wilson, Dennis G. ; Rodrigues, Silvio ; Segura, Carlos et al. / Summary of evolutionary computation for wind farm layout optimization. GECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion. Association for Computing Machinery, Inc, 2018. pp. 31-32

Bibtex

@inproceedings{c504dbca48b04cd188a4f164fe523b9e,
title = "Summary of evolutionary computation for wind farm layout optimization",
abstract = "This paper presents the results of the second edition of the Wind Farm Layout Optimization Competition, which was held at the 22nd Genetic and Evolutionary Computation COnference (GECCO) in 2015. During this competition, competitors were tasked with optimizing the layouts of ve generated wind farms based on a sim-plied cost of energy evaluation function of the wind farm layouts. Online and oine APIs were implemented in C++, Java, Matlab and Python for this competition to oer a common framework for the competitors. e top four approaches out of eight participating teams are presented in this paper and their results are compared. All of the competitors' algorithms use evolutionary computation.",
keywords = "Real-world problem, Wind farm layout optimization",
author = "Wilson, {Dennis G.} and Silvio Rodrigues and Carlos Segura and Ilya Loshchilov and Frank Huer and Buenl, {Guillermo L{\'o}pez} and Ahmed Kheiri and Ed Keedwell and Mario Ocampo-Pineda and Ender {\"O}zcan and Pea, {Sergio Ivvan Valdez} and Brian Goldman and Rionda, {Salvador Botello} and Arturo Hernndez-Aguirre and Kalyan Veeramachaneni and Sylvain Cussat-Blanc",
note = "{\textcopyright} The owners/authors, 2018. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in GECCO '18 Proceedings of the Genetic and Evolutionary Computation Conference Companion (2018) http://doi.acm.org/10.1145/3205651.3208208; 2018 Genetic and Evolutionary Computation Conference, GECCO 2018 ; Conference date: 15-07-2018 Through 19-07-2018",
year = "2018",
month = jul,
day = "6",
doi = "10.1145/3205651.3208208",
language = "English",
pages = "31--32",
booktitle = "GECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion",
publisher = "Association for Computing Machinery, Inc",

}

RIS

TY - GEN

T1 - Summary of evolutionary computation for wind farm layout optimization

AU - Wilson, Dennis G.

AU - Rodrigues, Silvio

AU - Segura, Carlos

AU - Loshchilov, Ilya

AU - Huer, Frank

AU - Buenl, Guillermo López

AU - Kheiri, Ahmed

AU - Keedwell, Ed

AU - Ocampo-Pineda, Mario

AU - Özcan, Ender

AU - Pea, Sergio Ivvan Valdez

AU - Goldman, Brian

AU - Rionda, Salvador Botello

AU - Hernndez-Aguirre, Arturo

AU - Veeramachaneni, Kalyan

AU - Cussat-Blanc, Sylvain

N1 - © The owners/authors, 2018. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in GECCO '18 Proceedings of the Genetic and Evolutionary Computation Conference Companion (2018) http://doi.acm.org/10.1145/3205651.3208208

PY - 2018/7/6

Y1 - 2018/7/6

N2 - This paper presents the results of the second edition of the Wind Farm Layout Optimization Competition, which was held at the 22nd Genetic and Evolutionary Computation COnference (GECCO) in 2015. During this competition, competitors were tasked with optimizing the layouts of ve generated wind farms based on a sim-plied cost of energy evaluation function of the wind farm layouts. Online and oine APIs were implemented in C++, Java, Matlab and Python for this competition to oer a common framework for the competitors. e top four approaches out of eight participating teams are presented in this paper and their results are compared. All of the competitors' algorithms use evolutionary computation.

AB - This paper presents the results of the second edition of the Wind Farm Layout Optimization Competition, which was held at the 22nd Genetic and Evolutionary Computation COnference (GECCO) in 2015. During this competition, competitors were tasked with optimizing the layouts of ve generated wind farms based on a sim-plied cost of energy evaluation function of the wind farm layouts. Online and oine APIs were implemented in C++, Java, Matlab and Python for this competition to oer a common framework for the competitors. e top four approaches out of eight participating teams are presented in this paper and their results are compared. All of the competitors' algorithms use evolutionary computation.

KW - Real-world problem

KW - Wind farm layout optimization

U2 - 10.1145/3205651.3208208

DO - 10.1145/3205651.3208208

M3 - Conference contribution/Paper

AN - SCOPUS:85051557430

SP - 31

EP - 32

BT - GECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion

PB - Association for Computing Machinery, Inc

T2 - 2018 Genetic and Evolutionary Computation Conference, GECCO 2018

Y2 - 15 July 2018 through 19 July 2018

ER -