Transfer function fitting using a continuous Ant Colony Optimization (ACO) algorithm

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A. Reineix
C. Guiffaut

Abstract

An original approach is proposed in order to achieve the  fitting of ultra-wideband complex frequency functions, such  as the complex impedances, by using the so-called ACO  (Ant Colony Optimization) methods. First, we present the  optimization principle of ACO, which originally was  dedicated to the combinatorial problems. Further on, the  extension to the continuous and mixed problems is  explained in more details. The interest in this approach is  proved by its ability to define practical constraints and  objectives, such as minimizing the number of filters used in  the model with respect to a fixed relative error. Finally, the  establishment of the model for the first and second order  filter types illustrates the power of the method and its  interest for the time-domain electromagnetic computation.

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How to Cite
Reineix, A., & Guiffaut, C. (2015). Transfer function fitting using a continuous Ant Colony Optimization (ACO) algorithm. Advanced Electromagnetics, 4(2), 1-8. https://doi.org/10.7716/aem.v4i2.283
Section
Research Articles

References


  1. S.S. Rao, "Engineering Optimization: Theory and Practive third Edition," A Wiley Interscience Publication, J. Wiley and Son, Inc. 1996. 

  2. D.E. Goldberg, "Genetic Algorithms in Search, Optimization and Machine Learning," Addison-Wesley. J. Holland, "Adaptation of the natural and artificial systems", Ann Arbor: University of Michigan Press, 1975. 

  3. K.A. De Jong and al, "Generation gap revisited. Fundation of genetic algorithms 2," edited by L.D. Whitley, pp 19-28. Morgan Kaufmann, 1993. 

  4. R. Azencott, "Simulated Annealing: Parallelization Techniques," John Wiley and Son, 1992. 

  5. J. Kennedy and Al., "Particle swarm optimization," Proc IEEE In'I. Confon Neural Networks, tome IV, pp 1942-1948, Piscataway, NJ: IEEE Service Center, 1995. 

  6. M. Dorigo, T. Stuzle, "Ant Colony Optimization", A Bradford Book, The MIT Press, Cambridge, Massachusetts, London, England, 2004. 

  7. M. Dorigo, "Optimization, Learning and Natural algorithms", PhD Thesis, Dipartimento di Elettronica Politecnico di Milano, Italy.

  8. M. Dorigo, L.M. Gambardella, "Ant Colonies for the Traveling Salesman Problem," Biosystems, tome 43, pp 73-81, 1997.
    View Article

  9. M. Dorigo, G. Di Caro, L.M. Gambardella, "Ant Algorithm for discrete optimization," Artificial life, 5, (2), pp: 137-172.
    View Article

  10. K. Socha and M. Dorigo, "Ant colony optimization for continuous domains," European Journal of Oprational Research, 185(2008), pp1155-1173.
    View Article

  11. K. Socha, "ACO for Continuous and Mixed-Variable Optimization. In Ant Colony Optimization and Swarm Intelligence," M.Dorigo, M. Biratttari, C. Blum, L.M. Gambardella, F. Mondada, T. Stutzle, Eds; 4th Workshop ANTS2004 Bressels, Belgium, September 2004, Proceedings, vol 3172 of Lecture Notes in Computer Science, pp25-36, Springer: Berlin-Heigelberg, 2004.

  12. K. Socha, M. Dorigo, "Ant Colony Optimization for continuous Domains," European Journal of Operational Research 185 (2008), pp: 1155-1173.

  13. K. Socha, "Ant Colony Optimization for Continuous an Mixed-Variable Domains," Thesis of the Université Libre de Bruxelles, Belgium.

  14. M. Bjorn Gustavsen, L.F. Adam Semlyen, " Rational Approximation of frequency time domain responses by Vector Fitting", IEEE Trans. on Power Delivery, vol 14, N°3, July 1999, pp1052-1061.
    View Article

  15. M. C. O Jansson, S. P. O Ljung, M. G. Bäckström, B.I. Wahlgren, "Efficient implementation of a submodel for composite materials to be combined with the FDTD-algorithm," IEEE Trans. Magn., vol. 30, no. 4, pp. 3188–3191, Sep. 1994.
    View Article