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Multi-criterion Evolutionary Algorithm with Model of the Immune System to Handle Constraints for Task Assignments

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Artificial Intelligence and Soft Computing - ICAISC 2004 (ICAISC 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3070))

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Abstract

In this paper, an evolutionary algorithm based on an immune system activity to handle constraints is discussed for three-criteria optimisation problem of finding a set of Pareto-suboptimal task assignments in parallel systems. This approach deals with a modified genetic algorithm cooperating with a main evolutionary algorithm. An immune system activity is emulated by a modified genetic algorithm to handle constraints. Some numerical results are submitted.

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References

  1. Balicki, J., Kitowski, Z.: Multicriteria Evolutionary Algorithm with Tabu Search for Task Assignment. In: Zitzler, E., Deb, K., Thiele, L., Coello Coello, C.A., Corne, D.W. (eds.) EMO 2001. LNCS, vol. 1993, pp. 373–384. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  2. Coello Coello, C.A., Cortes, N.C.: Use of Emulations of the Immune System to Handle Constraints in Evolutionary Algorithms, Knowledge and Information Systems. An International Journal 1, 1–12 (2001)

    Google Scholar 

  3. Coello Coello, C.A., Van Veldhuizen, D.A., Lamont, G.B.: Evolutionary Algorithms for Solving Multi-Objective Problems. Kluwer Academic Publishers, New York (2002)

    MATH  Google Scholar 

  4. Deb, K.: Multi-Objective Optimization using Evolutionary Algorithms. John Wiley & Sons, Chichester (2001)

    MATH  Google Scholar 

  5. D’haeseleer, P., et al.: An Immunological Approach to Change Detection. In: Proc. of IEEE Symposium on Research in Security and Privacy, Oakland (1996)

    Google Scholar 

  6. Farmer, J.D., Packard, N.H., Perelson, A.S.: The Immune System, Adaptation, and Machine Learning. Physica D 22, 187–204 (1986)

    Article  MathSciNet  Google Scholar 

  7. Forrest, S., Perelson, A.S.: Genetic Algorithms and the Immune System. LNCS, pp. 320–325 (1991)

    Google Scholar 

  8. Helman, P., Forrest, S.: An Efficient Algorithm for Generating Random Antibody Strings. Technical Report CS-94-07, The University of New Mexico, Albuquerque (1994)

    Google Scholar 

  9. Jerne, N.K.: The Immune System. Scientific American 229(1), 52–60 (1973)

    Article  Google Scholar 

  10. Kim, J., Bentley, P.J.: Immune Memory in the Dynamic Clonal Selection Algorithm. In: Proc. of the First Int. Conf. on Artificial Immune Systems, Canterbury, pp. 57–65 (2002)

    Google Scholar 

  11. Koziel, S., Michalewicz, Z.: Evolutionary Algorithms, Homomorphous mapping, and Constrained Parameter Optimisation. Evolutionary Computation 7, 19–44 (1999)

    Article  Google Scholar 

  12. Smith, D.: Towards a Model of Associative Recall in Immunological Memory. Technical Report 94-9, University of New Mexico, Albuquerque (1994)

    Google Scholar 

  13. Weglarz, J. (ed.): Recent Advances in Project Scheduling. Kluwer Academic Publishers, Dordrecht (1998)

    Google Scholar 

  14. Wierzchon, S.T.: Generating Optimal Repertoire of Antibody Strings in an Artificial Immune System. In: Klopotek, M., Michalewicz, M., Wierzchon, S.T. (eds.) Intelligent Information Systems, pp. 119–133. Springer, Heidelberg (2000)

    Google Scholar 

  15. Zitzler, E., Deb, K., Thiele, L.: Comparison of Multiobjective Evolutionary Algorithms: Empirical Results. Evolutionary Computation 8(2), 173–195 (2000)

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Computer Science Department, The Naval University of Gdynia, ul. Śmidowicza 69, 81-103, Gdynia, Poland

    Jerzy Balicki

Authors
  1. Jerzy Balicki
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Editor information

Editors and Affiliations

  1. Department of Artificial Intelligence, Academy of Humanities and Economics, Poland

    Leszek Rutkowski

  2. German Research Center of Artificial Intelligence (DFKI), Germany

    Jörg H. Siekmann

  3. Institute of Automatics, AGH University of Science and Technology, Al. Mickiewicza 30, PL-30-059, Kraków, Poland

    Ryszard Tadeusiewicz

  4. Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, Initiative in Soft Computing (BISC), 94720-1776, Berkeley, CA

    Lotfi A. Zadeh

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© 2004 Springer-Verlag Berlin Heidelberg

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Balicki, J. (2004). Multi-criterion Evolutionary Algorithm with Model of the Immune System to Handle Constraints for Task Assignments. In: Rutkowski, L., Siekmann, J.H., Tadeusiewicz, R., Zadeh, L.A. (eds) Artificial Intelligence and Soft Computing - ICAISC 2004. ICAISC 2004. Lecture Notes in Computer Science(), vol 3070. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24844-6_57

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  • DOI: https://doi.org/10.1007/978-3-540-24844-6_57

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22123-4

  • Online ISBN: 978-3-540-24844-6

  • eBook Packages: Springer Book Archive

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