Analysis of scalable parallel evolutionary algorithms

Jun HE; Xin YAO

doi:10.1109/CEC.2006.1688298

Analysis of scalable parallel evolutionary algorithms

Jun HE
, Xin YAO

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

9 Citations (Scopus)

Abstract

Inherent parallelism is regarded as one of the most important advantages of evolutionary algorithms. This paper aims at makin g an initial study on the speedup of scalable parallel evolutionary algorithms. First the scalable parallel evolutionary algo rithms are described; then the speedup of such scalable algorithms is defined based on the first hitting time; Using the new definition, the relationship between population diversity and superlinear speedup is analyzed; finally a case study demonstra tes how population diversity plays a crucial role in generating the superlinear speedup. © 2006 IEEE.

Original language	English
Title of host publication	2006 IEEE Congress on Evolutionary Computation, CEC 2006
Publisher	IEEE
Pages	120-127
Number of pages	8
ISBN (Print)	9780780394872
DOIs	https://doi.org/10.1109/CEC.2006.1688298
Publication status	Published - 2006
Externally published	Yes

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10.1109/CEC.2006.1688298

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title = "Analysis of scalable parallel evolutionary algorithms",

abstract = "Inherent parallelism is regarded as one of the most important advantages of evolutionary algorithms. This paper aims at makin g an initial study on the speedup of scalable parallel evolutionary algorithms. First the scalable parallel evolutionary algo rithms are described; then the speedup of such scalable algorithms is defined based on the first hitting time; Using the new definition, the relationship between population diversity and superlinear speedup is analyzed; finally a case study demonstra tes how population diversity plays a crucial role in generating the superlinear speedup. {\textcopyright} 2006 IEEE.",

author = "Jun HE and Xin YAO",

year = "2006",

doi = "10.1109/CEC.2006.1688298",

language = "English",

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AU - HE, Jun

AU - YAO, Xin

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N2 - Inherent parallelism is regarded as one of the most important advantages of evolutionary algorithms. This paper aims at makin g an initial study on the speedup of scalable parallel evolutionary algorithms. First the scalable parallel evolutionary algo rithms are described; then the speedup of such scalable algorithms is defined based on the first hitting time; Using the new definition, the relationship between population diversity and superlinear speedup is analyzed; finally a case study demonstra tes how population diversity plays a crucial role in generating the superlinear speedup. © 2006 IEEE.

AB - Inherent parallelism is regarded as one of the most important advantages of evolutionary algorithms. This paper aims at makin g an initial study on the speedup of scalable parallel evolutionary algorithms. First the scalable parallel evolutionary algo rithms are described; then the speedup of such scalable algorithms is defined based on the first hitting time; Using the new definition, the relationship between population diversity and superlinear speedup is analyzed; finally a case study demonstra tes how population diversity plays a crucial role in generating the superlinear speedup. © 2006 IEEE.

UR - https://www.scopus.com/pages/publications/34547374334

U2 - 10.1109/CEC.2006.1688298

DO - 10.1109/CEC.2006.1688298

M3 - Conference paper (refereed)

SN - 9780780394872

SP - 120

EP - 127

BT - 2006 IEEE Congress on Evolutionary Computation, CEC 2006

PB - IEEE

ER -

Analysis of scalable parallel evolutionary algorithms

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