Clonal selection with immune dominance and anergy based multiobjective optimization

Licheng Jiao; Maoguo Gong; Ronghua Shang; Haifeng Du; Bin Lu

doi:10.1007/978-3-540-31880-4_33

Clonal selection with immune dominance and anergy based multiobjective optimization

Licheng Jiao
, Maoguo Gong
, Ronghua Shang
, Haifeng Du
, Bin Lu

公共政策与管理学院

Xidian University

科研成果: 期刊稿件 › 会议文章 › 同行评审

70 引用（Scopus）

摘要

Based on the concept of Immunodominance and Antibody Clonal Selection Theory, we propose a new artificial immune system algorithm, Immune Dominance Clonal Multiobjective Algorithm (IDCMA). The influences of main parameters are analyzed empirically. The simulation comparisons among IDCMA, the Random-Weight Genetic Algorithm and the Strength Pareto Evolutionary Algorithm show that when low-dimensional multiobjective problems are concerned, IDCMA has the best performance in metrics such as Spacing and Coverage of Two Sets.

源语言	英语
页（从-至）	474-489
页数	16
期刊	Lecture Notes in Computer Science
卷	3410
DOI	https://doi.org/10.1007/978-3-540-31880-4_33
出版状态	已出版 - 2005
活动	Third International Conference on Evolutionary Multi-Criterion Optimization, EMO 2005 - Guanajuato, 墨西哥期限: 9 3月 2005 → 11 3月 2005

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abstract = "Based on the concept of Immunodominance and Antibody Clonal Selection Theory, we propose a new artificial immune system algorithm, Immune Dominance Clonal Multiobjective Algorithm (IDCMA). The influences of main parameters are analyzed empirically. The simulation comparisons among IDCMA, the Random-Weight Genetic Algorithm and the Strength Pareto Evolutionary Algorithm show that when low-dimensional multiobjective problems are concerned, IDCMA has the best performance in metrics such as Spacing and Coverage of Two Sets.",

author = "Licheng Jiao and Maoguo Gong and Ronghua Shang and Haifeng Du and Bin Lu",

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journal = "Lecture Notes in Computer Science",

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T1 - Clonal selection with immune dominance and anergy based multiobjective optimization

AU - Jiao, Licheng

AU - Gong, Maoguo

AU - Shang, Ronghua

AU - Du, Haifeng

AU - Lu, Bin

PY - 2005

Y1 - 2005

N2 - Based on the concept of Immunodominance and Antibody Clonal Selection Theory, we propose a new artificial immune system algorithm, Immune Dominance Clonal Multiobjective Algorithm (IDCMA). The influences of main parameters are analyzed empirically. The simulation comparisons among IDCMA, the Random-Weight Genetic Algorithm and the Strength Pareto Evolutionary Algorithm show that when low-dimensional multiobjective problems are concerned, IDCMA has the best performance in metrics such as Spacing and Coverage of Two Sets.

AB - Based on the concept of Immunodominance and Antibody Clonal Selection Theory, we propose a new artificial immune system algorithm, Immune Dominance Clonal Multiobjective Algorithm (IDCMA). The influences of main parameters are analyzed empirically. The simulation comparisons among IDCMA, the Random-Weight Genetic Algorithm and the Strength Pareto Evolutionary Algorithm show that when low-dimensional multiobjective problems are concerned, IDCMA has the best performance in metrics such as Spacing and Coverage of Two Sets.

UR - https://www.scopus.com/pages/publications/24344467542

U2 - 10.1007/978-3-540-31880-4_33

DO - 10.1007/978-3-540-31880-4_33

M3 - 会议文章

AN - SCOPUS:24344467542

SN - 0302-9743

VL - 3410

SP - 474

EP - 489

JO - Lecture Notes in Computer Science

JF - Lecture Notes in Computer Science

T2 - Third International Conference on Evolutionary Multi-Criterion Optimization, EMO 2005

Y2 - 9 March 2005 through 11 March 2005

ER -

Clonal selection with immune dominance and anergy based multiobjective optimization

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