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VIS: An artificial immune network for multi-objective optimization.

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Title: VIS: An artificial immune network for multi-objective optimization.
Authors: Freschi, Fabio1 fabio.freschi@polito.it, Repetto, Maurizio1
Source: Engineering Optimization. Dec2006, Vol. 38 Issue 8, p975-996. 22p. 1 Diagram, 8 Charts, 8 Graphs.
Subjects: Computer simulation of immune system, Structural optimization, Multidisciplinary design optimization, Algorithms, Evolutionary computation, Multiple criteria decision making
Abstract: The aim of this work is to propose and validate a novel multi-objective optimization algorithm based on the emulation of the behaviour of the immune system. The rationale of this work is that the artificial immune system has, in its elementary structure, the main features required by other multi-objective evolutionary algorithms described in the literature, such as diversity preservation, memory, adaptivity, and elitism. The proposed approach is compared with three multi-objective evolutionary algorithms that are representative of the state of the art in multi-objective optimization. Algorithms are tested on six standard problems (both unconstrained and constrained) and comparisons are carried out using three different metrics. Results show that the proposed approach has very good performances and can become a valid alternative to standard algorithms for solving multi-objective optimization problems. [ABSTRACT FROM AUTHOR]
Copyright of Engineering Optimization is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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PubType: Academic Journal
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  Data: VIS: An artificial immune network for multi-objective optimization.
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  Data: <searchLink fieldCode="JN" term="%22Engineering+Optimization%22">Engineering Optimization</searchLink>. Dec2006, Vol. 38 Issue 8, p975-996. 22p. 1 Diagram, 8 Charts, 8 Graphs.
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  Data: <searchLink fieldCode="DE" term="%22Computer+simulation+of+immune+system%22">Computer simulation of immune system</searchLink><br /><searchLink fieldCode="DE" term="%22Structural+optimization%22">Structural optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Multidisciplinary+design+optimization%22">Multidisciplinary design optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Evolutionary+computation%22">Evolutionary computation</searchLink><br /><searchLink fieldCode="DE" term="%22Multiple+criteria+decision+making%22">Multiple criteria decision making</searchLink>
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  Data: The aim of this work is to propose and validate a novel multi-objective optimization algorithm based on the emulation of the behaviour of the immune system. The rationale of this work is that the artificial immune system has, in its elementary structure, the main features required by other multi-objective evolutionary algorithms described in the literature, such as diversity preservation, memory, adaptivity, and elitism. The proposed approach is compared with three multi-objective evolutionary algorithms that are representative of the state of the art in multi-objective optimization. Algorithms are tested on six standard problems (both unconstrained and constrained) and comparisons are carried out using three different metrics. Results show that the proposed approach has very good performances and can become a valid alternative to standard algorithms for solving multi-objective optimization problems. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Engineering Optimization is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1080/03052150600880706
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      – Code: eng
        Text: English
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        PageCount: 22
        StartPage: 975
    Subjects:
      – SubjectFull: Computer simulation of immune system
        Type: general
      – SubjectFull: Structural optimization
        Type: general
      – SubjectFull: Multidisciplinary design optimization
        Type: general
      – SubjectFull: Algorithms
        Type: general
      – SubjectFull: Evolutionary computation
        Type: general
      – SubjectFull: Multiple criteria decision making
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      – TitleFull: VIS: An artificial immune network for multi-objective optimization.
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              M: 12
              Text: Dec2006
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              Y: 2006
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              Value: 38
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