Parallel Evolutionary Algorithm with Interleaving Generations

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F17%3A00477041" target="_blank" >RIV/67985807:_____/17:00477041 - isvavai.cz</a>

Alternative codes found

RIV/00216208:11320/17:10361034

Result on the web

<a href="http://dx.doi.org/10.1145/3071178.3071309" target="_blank" >http://dx.doi.org/10.1145/3071178.3071309</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1145/3071178.3071309" target="_blank" >10.1145/3071178.3071309</a>

Result language

angličtina

Original language name

Parallel Evolutionary Algorithm with Interleaving Generations

Original language description

We present a parallel evolutionary algorithm with interleaving generations. The algorithm uses a careful analysis of genetic operators and selection in order to evaluate individuals from following generations while the current generation is still not completely evaluated. This brings significant advantages in cases where each fitness evaluation takes different amount of time, the evaluations are performed in parallel, and a traditional generational evolutionary algorithm has to wait for all evaluations to finish. The proposed algorithm provides better utilization of computational resources in these cases. Moreover, the algorithm is functionally equivalent to the generational evolutionary algorithm, and thus it does not have any evaluation time bias, which is often present in asynchronous evolutionary algorithms. The proposed algorithm is tested in a series of simple experiments and its effectiveness is compared to the effectiveness of the generational evolutionary algorithm in terms of CPU utilization.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/GA15-19877S" target="_blank" >GA15-19877S: Automated Knowledge and Plan Modeling for Autonomous Robots</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2017

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

GECCO 2017. Proceedings of the 2017 Genetic and Evolutionary Computation Conference

ISBN

978-1-4503-4920-8

ISSN

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e-ISSN

—

Number of pages

8

Pages from-to

865-872

Publisher name

ACM

Place of publication

New York

Event location

Berlin

Event date

Jul 15, 2017

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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