An improved niche genetic algorithm

Min Zhang; Xue Zhang; Yun Tao Zhang; Jin Ming

doi:10.4028/www.scientific.net/AMM.380-384.1444

An improved niche genetic algorithm

Min Zhang
, Xue Zhang
, Yun Tao Zhang
, Jin Ming

Harbin Institute of Technology Weihai

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

Abstract

As a result of poor local research performance and short of the population diversity in niche genetic algorithm(NGA), an improved niche genetic algorithm(I-NGA) is presented in this paper. The algorithm adopts migration strategy, grading gradient method and gene equilibrium strategy, and it has better performance on accelerating the convergence rate and increasing the population diversity. This approach is used in Camel function for confirming. Through comparisons to NGA and I-NGA, the improved algorithm shows its better optimization.

Original language	English
Title of host publication	Vehicle, Mechatronics and Information Technologies
Pages	1444-1447
Number of pages	4
DOIs	https://doi.org/10.4028/www.scientific.net/AMM.380-384.1444
State	Published - 2013
Externally published	Yes
Event	2013 International Conference on Vehicle and Mechanical Engineering and Information Technology, VMEIT 2013 - Zhengzhou, Henan, China Duration: 17 Aug 2013 → 18 Aug 2013

Publication series

Name	Applied Mechanics and Materials
Volume	380-384
ISSN (Print)	1660-9336
ISSN (Electronic)	1662-7482

Conference

Conference	2013 International Conference on Vehicle and Mechanical Engineering and Information Technology, VMEIT 2013
Country/Territory	China
City	Zhengzhou, Henan
Period	17/08/13 → 18/08/13

Keywords

Gene equilibrium strategy
Grading gradient method
Migration strategy
NGA

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10.4028/www.scientific.net/AMM.380-384.1444

Cite this

@inproceedings{facf973721e74e908794e2ffa94d6502,

title = "An improved niche genetic algorithm",

abstract = "As a result of poor local research performance and short of the population diversity in niche genetic algorithm(NGA), an improved niche genetic algorithm(I-NGA) is presented in this paper. The algorithm adopts migration strategy, grading gradient method and gene equilibrium strategy, and it has better performance on accelerating the convergence rate and increasing the population diversity. This approach is used in Camel function for confirming. Through comparisons to NGA and I-NGA, the improved algorithm shows its better optimization.",

keywords = "Gene equilibrium strategy, Grading gradient method, Migration strategy, NGA",

author = "Min Zhang and Xue Zhang and Zhang, \{Yun Tao\} and Jin Ming",

year = "2013",

doi = "10.4028/www.scientific.net/AMM.380-384.1444",

language = "英语",

isbn = "9783037858202",

series = "Applied Mechanics and Materials",

pages = "1444--1447",

booktitle = "Vehicle, Mechatronics and Information Technologies",

note = "2013 International Conference on Vehicle and Mechanical Engineering and Information Technology, VMEIT 2013 ; Conference date: 17-08-2013 Through 18-08-2013",

}

Zhang, M, Zhang, X, Zhang, YT & Ming, J 2013, An improved niche genetic algorithm. in Vehicle, Mechatronics and Information Technologies. Applied Mechanics and Materials, vol. 380-384, pp. 1444-1447, 2013 International Conference on Vehicle and Mechanical Engineering and Information Technology, VMEIT 2013, Zhengzhou, Henan, China, 17/08/13. https://doi.org/10.4028/www.scientific.net/AMM.380-384.1444

TY - GEN

T1 - An improved niche genetic algorithm

AU - Zhang, Min

AU - Zhang, Xue

AU - Zhang, Yun Tao

AU - Ming, Jin

PY - 2013

Y1 - 2013

N2 - As a result of poor local research performance and short of the population diversity in niche genetic algorithm(NGA), an improved niche genetic algorithm(I-NGA) is presented in this paper. The algorithm adopts migration strategy, grading gradient method and gene equilibrium strategy, and it has better performance on accelerating the convergence rate and increasing the population diversity. This approach is used in Camel function for confirming. Through comparisons to NGA and I-NGA, the improved algorithm shows its better optimization.

AB - As a result of poor local research performance and short of the population diversity in niche genetic algorithm(NGA), an improved niche genetic algorithm(I-NGA) is presented in this paper. The algorithm adopts migration strategy, grading gradient method and gene equilibrium strategy, and it has better performance on accelerating the convergence rate and increasing the population diversity. This approach is used in Camel function for confirming. Through comparisons to NGA and I-NGA, the improved algorithm shows its better optimization.

KW - Gene equilibrium strategy

KW - Grading gradient method

KW - Migration strategy

KW - NGA

UR - https://www.scopus.com/pages/publications/84884836299

U2 - 10.4028/www.scientific.net/AMM.380-384.1444

DO - 10.4028/www.scientific.net/AMM.380-384.1444

M3 - 会议稿件

AN - SCOPUS:84884836299

SN - 9783037858202

T3 - Applied Mechanics and Materials

SP - 1444

EP - 1447

BT - Vehicle, Mechatronics and Information Technologies

T2 - 2013 International Conference on Vehicle and Mechanical Engineering and Information Technology, VMEIT 2013

Y2 - 17 August 2013 through 18 August 2013

ER -

An improved niche genetic algorithm

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