Benchmarking the (1+1) evolution strategy with one-fifth success rule on the BBOB-2009 function testbed

Anne Auger

doi:10.1145/1570256.1570342

Benchmarking the (1+1) evolution strategy with one-fifth success rule on the BBOB-2009 function testbed

Anne Auger

INRIA

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In this paper, we benchmark the (1+1) Evolution Strategy (ES) with one-fifth success rule which is one of the first and simplest adaptive search algorithms proposed for optimization. The benchmarking is conducted on the noise-free BBOB-2009 testbed. We implement a restart version of the algorithm and conduct for each run 106 times the dimension of the search space function evaluations.

Original language	English
Title of host publication	Proceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009
Publisher	Association for Computing Machinery
Pages	2447-2452
Number of pages	6
ISBN (Print)	9781605583259
DOIs	https://doi.org/10.1145/1570256.1570342
Publication status	Published - 1 Jan 2009
Externally published	Yes
Event	11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009 - Montreal, QC, Canada Duration: 8 Jul 2009 → 12 Jul 2009

Publication series

Name	Proceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009
Volume	2009-January

Conference

Conference	11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009
Country/Territory	Canada
City	Montreal, QC
Period	8/07/09 → 12/07/09

Keywords

adaptive search
benchmarking
black-box optimization
evolution strategies
evolutionary computation
one-fifth success rule

Access to Document

10.1145/1570256.1570342

Cite this

Auger, A. (2009). Benchmarking the (1+1) evolution strategy with one-fifth success rule on the BBOB-2009 function testbed. In Proceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009 (pp. 2447-2452). (Proceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009; Vol. 2009-January). Association for Computing Machinery. https://doi.org/10.1145/1570256.1570342

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title = "Benchmarking the (1+1) evolution strategy with one-fifth success rule on the BBOB-2009 function testbed",

abstract = "In this paper, we benchmark the (1+1) Evolution Strategy (ES) with one-fifth success rule which is one of the first and simplest adaptive search algorithms proposed for optimization. The benchmarking is conducted on the noise-free BBOB-2009 testbed. We implement a restart version of the algorithm and conduct for each run 106 times the dimension of the search space function evaluations.",

keywords = "adaptive search, benchmarking, black-box optimization, evolution strategies, evolutionary computation, one-fifth success rule",

author = "Anne Auger",

note = "Publisher Copyright: {\textcopyright} 2009 ACM.; 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009 ; Conference date: 08-07-2009 Through 12-07-2009",

year = "2009",

month = jan,

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doi = "10.1145/1570256.1570342",

language = "English",

isbn = "9781605583259",

series = "Proceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009",

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Auger, A 2009, Benchmarking the (1+1) evolution strategy with one-fifth success rule on the BBOB-2009 function testbed. in Proceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009. Proceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009, vol. 2009-January, Association for Computing Machinery, pp. 2447-2452, 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009, Montreal, QC, Canada, 8/07/09. https://doi.org/10.1145/1570256.1570342

Benchmarking the (1+1) evolution strategy with one-fifth success rule on the BBOB-2009 function testbed. / Auger, Anne.
Proceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009. Association for Computing Machinery, 2009. p. 2447-2452 (Proceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009; Vol. 2009-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - In this paper, we benchmark the (1+1) Evolution Strategy (ES) with one-fifth success rule which is one of the first and simplest adaptive search algorithms proposed for optimization. The benchmarking is conducted on the noise-free BBOB-2009 testbed. We implement a restart version of the algorithm and conduct for each run 106 times the dimension of the search space function evaluations.

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KW - black-box optimization

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PB - Association for Computing Machinery

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Auger A. Benchmarking the (1+1) evolution strategy with one-fifth success rule on the BBOB-2009 function testbed. In Proceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009. Association for Computing Machinery. 2009. p. 2447-2452. (Proceedings of the 11th Annual Genetic and Evolutionary Computation Conference, GECCO-2009). doi: 10.1145/1570256.1570342

Benchmarking the (1+1) evolution strategy with one-fifth success rule on the BBOB-2009 function testbed

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Keywords

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