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A Concentration-Based Artificial Immune Network for Multi-objective Optimization

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Evolutionary Multi-Criterion Optimization (EMO 2011)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6576))

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Abstract

Until recently, the main focus of researchers that develop algorithms for evolutionary multi-objective optimization has been the creation of mechanisms capable of obtaining sets of solutions that are as close as possible to the true Pareto front of the problem and also as diverse as possible in the objective space, to properly cover such front. However, an adequate maintenance of diversity in the decision space is also important, to efficiently solve several classes of problems and even to facilitate the post-optimization decision making process. This aspect has been widely studied in evolutionary single-objective optimization, what led to the development of several diversity maintenance techniques. Among them, the recently proposed concentration-based artificial immune network (cob-aiNet), which is capable of self-regulating the population size, presented promising results in multimodal problems. So, it is extended here to deal with multi-objective problems that require a proper maintenance of diversity in the decision space.

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Authors and Affiliations

  1. Laboratory of Bioinformatics and Bioinspired Computing (LBiC), Department of Computer Engineering and Industrial Automation (DCA), School of Electrical and Computer Engineering (FEEC), University of Campinas (Unicamp), Campinas, SP, Brazil

    Guilherme Palermo Coelho & Fernando J. Von Zuben

Authors
  1. Guilherme Palermo Coelho
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  2. Fernando J. Von Zuben
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Editor information

Editors and Affiliations

  1. Department of Mathematics, Federal University of Minas Gerais, Av. Antônio Carlos 6627, 31270-901, Belo Horizonte, MG, Brazil

    Ricardo H. C. Takahashi

  2. Department of Mechanical Engineering, Indian Institute of Technology Kanpur, 208 016, Kanpur, India

    Kalyanmoy Deb

  3. Department of Computer Engineering, Centro Federal de Educaçao Tecnológica de Minas Gerais, Av. Amazonas 5253, 30421-169, Belo Horizonte, MG, Brazil

    Elizabeth F. Wanner

  4. Faculty of Economics, University of Catania, Corso Italia 55, 95129, Catania, Italy

    Salvatore Greco

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© 2011 Springer-Verlag Berlin Heidelberg

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Coelho, G.P., Von Zuben, F.J. (2011). A Concentration-Based Artificial Immune Network for Multi-objective Optimization. In: Takahashi, R.H.C., Deb, K., Wanner, E.F., Greco, S. (eds) Evolutionary Multi-Criterion Optimization. EMO 2011. Lecture Notes in Computer Science, vol 6576. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19893-9_24

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  • DOI: https://doi.org/10.1007/978-3-642-19893-9_24

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-19892-2

  • Online ISBN: 978-3-642-19893-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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