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Performance assessment of an artificial immune system multiobjective optimizer by two improved metrics

  • Maoguo Gong
  • , Ronghua Shang
  • , Licheng Jiao
  • , Haifeng Du
  • , Bin Lu
  • Xidian University

科研成果: 书/报告/会议事项章节会议稿件同行评审

1 引用 (Scopus)

摘要

In this study, we introduce two improved assessment metrics of multiobjective optimizers, Nondominated Ratio and Spacing Distribution, and analyze their rationality and validity. Based on the concept of Immunodominance and Antibody Clonal Selection Theory, a novel multiobjective optimization algorithm, Immune Dominance Clonal Multiobjective Algorithm (IDCMA), is put forward. The simulation comparisons between IDCMA and the Strength Pareto Evolutionary Algorithm show that IDCMA has the best performance in popular metrics such as Spacing, Coverage of Two Sets and the two new metrics presented in this paper when low-dimensional multiobjective problems are concerned. The statistical results of the four metrics also show that Spacing Distribution conquers some limitations of Spacing triumphantly, and Nondominated Ratio conquers the limitation of Coverage of Two Sets that only compared between two sets.

源语言英语
主期刊名GECCO 2005 - Genetic and Evolutionary Computation Conference
编辑H.G. Beyer, U.M. O'Reilly, D. Arnold, W. Banzhaf, C. Blum, E.W. Bonabeau, E. Cantu-Paz, D. Dasgupta, K. Deb, al et al
373-374
页数2
DOI
出版状态已出版 - 2005
活动GECCO 2005 - Genetic and Evolutionary Computation Conference - Washington, D.C., 美国
期限: 25 6月 200529 6月 2005

出版系列

姓名GECCO 2005 - Genetic and Evolutionary Computation Conference

会议

会议GECCO 2005 - Genetic and Evolutionary Computation Conference
国家/地区美国
Washington, D.C.
时期25/06/0529/06/05

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