Study on guiding immune algorithm

Ning Sun; Xi Yuan Peng; Li Yan Qiao

Study on guiding immune algorithm

Ning Sun^*
, Xi Yuan Peng
, Li Yan Qiao

^*Corresponding author for this work

School of Electronics and Information Engineering

Harbin Institute of Technology

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

Immune algorithm is an intelligent system, and shows great potential in optimization. However, as the local search of immune optimizer is of some blindness, its efficiency is limited. Guiding immune optimization algorithm is proposed, which introduces sociality to immune optimization algorithm, and accordingly improves convergence speed. The related parameters are also discussed. Analysis and simulation results show that guiding immune optimizer effectively improves the searching speed of immune algorithm as well as ensures the high succeed probability.

Original language	English
Pages (from-to)	2401-2405
Number of pages	5
Journal	Tien Tzu Hsueh Pao/Acta Electronica Sinica
Volume	33
Issue number	SUPPL.
State	Published - Dec 2005

Keywords

Guiding immune algorithm
Immune algorithm
Optimize algorithm

Cite this

@article{4ecc6133d41e409da5a905d87f0654cb,

title = "Study on guiding immune algorithm",

abstract = "Immune algorithm is an intelligent system, and shows great potential in optimization. However, as the local search of immune optimizer is of some blindness, its efficiency is limited. Guiding immune optimization algorithm is proposed, which introduces sociality to immune optimization algorithm, and accordingly improves convergence speed. The related parameters are also discussed. Analysis and simulation results show that guiding immune optimizer effectively improves the searching speed of immune algorithm as well as ensures the high succeed probability.",

keywords = "Guiding immune algorithm, Immune algorithm, Optimize algorithm",

author = "Ning Sun and Peng, \{Xi Yuan\} and Qiao, \{Li Yan\}",

year = "2005",

month = dec,

language = "英语",

volume = "33",

pages = "2401--2405",

journal = "Tien Tzu Hsueh Pao/Acta Electronica Sinica",

issn = "0372-2112",

publisher = "Chinese Institute of Electronics",

number = "SUPPL.",

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TY - JOUR

T1 - Study on guiding immune algorithm

AU - Sun, Ning

AU - Peng, Xi Yuan

AU - Qiao, Li Yan

PY - 2005/12

Y1 - 2005/12

N2 - Immune algorithm is an intelligent system, and shows great potential in optimization. However, as the local search of immune optimizer is of some blindness, its efficiency is limited. Guiding immune optimization algorithm is proposed, which introduces sociality to immune optimization algorithm, and accordingly improves convergence speed. The related parameters are also discussed. Analysis and simulation results show that guiding immune optimizer effectively improves the searching speed of immune algorithm as well as ensures the high succeed probability.

AB - Immune algorithm is an intelligent system, and shows great potential in optimization. However, as the local search of immune optimizer is of some blindness, its efficiency is limited. Guiding immune optimization algorithm is proposed, which introduces sociality to immune optimization algorithm, and accordingly improves convergence speed. The related parameters are also discussed. Analysis and simulation results show that guiding immune optimizer effectively improves the searching speed of immune algorithm as well as ensures the high succeed probability.

KW - Guiding immune algorithm

KW - Immune algorithm

KW - Optimize algorithm

UR - https://www.scopus.com/pages/publications/33745665568

M3 - 文章

AN - SCOPUS:33745665568

SN - 0372-2112

VL - 33

SP - 2401

EP - 2405

JO - Tien Tzu Hsueh Pao/Acta Electronica Sinica

JF - Tien Tzu Hsueh Pao/Acta Electronica Sinica

IS - SUPPL.

ER -

Study on guiding immune algorithm

Abstract

Keywords

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