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

Published: 25 June 2005 Publication History

Abstract

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.

References

[1]
Dasgupta, D., Forrest, S. Artificial immune systems in industrial applications. In IPMM '99. Proceedings of the Second International Conference on Intelligent Processing and Manufacturing of Materials. IEEE press, 1999. 257--267.
[2]
Jiao, L.C., Gong, M.G., Shang, R.H., DU, H.F., Lu, B. Clonal Selection with Immune Dominance and Anergy Based Multiobjective Optimization. In Proceedings of the Third International Conference on Evolutionary Multi-Criterion Optimization, EMO 2005, Guanajuato, Mexico, 2005, 474--489.
[3]
Schott, J.R. Fault Tolerant Design Using Single and Multictiteria Gentetic Algorithm Optimization. Master's thesis, Massachusetts Institute of Technology, Cambridge, Massachusetts, May 1995.
[4]
Van Veldhuizen, D.A. Multiobjective Evolutionary Algorithms: Classification, Analyses, and New Innovations. PhD thesis. Presented to the Faculty of the Graduate School of Engineering of he Air Force Institute of Technology. Air University. USA. AFIT/DS/ENG.
[5]
Zitzler, E. Evolutionary Algorithms for Multiobjective Optimization: Methods and Applications. A dissertation submitted to the Swiss Federal Institute of Technology Zurich for the degree of Doctor of Technical Sciences. Diss. Eth No. 13398. 1999.
[6]
Zitzler, E., Laumanns, M. and Thiele, L. SPEA2: Improving the Strength Pareto Evolutionary Algorithm. Technical Report 103, Computer Engineering and Communication Networks Lab (TIK), Swiss Federal Institute of Technology (ETH) Zurich, Gloriastrasse 35, CH-8092 Zurich, May 2001.

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

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    cover image ACM Conferences
    GECCO '05: Proceedings of the 7th annual conference on Genetic and evolutionary computation
    June 2005
    2272 pages
    ISBN:1595930108
    DOI:10.1145/1068009
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Publication History

    Published: 25 June 2005

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    Author Tags

    1. artificial immune system
    2. clonal selection
    3. immune dominance
    4. multiobjective optimization
    5. performance assessment

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