eprintid: 563 rev_number: 6 eprint_status: archive userid: 5 dir: disk0/00/00/05/63 datestamp: 2004-10-25 lastmod: 2013-07-04 15:03:57 status_changed: 2013-07-04 15:03:57 type: techreport metadata_visibility: show item_issues_count: 0 creators_name: Bort, Emmanuele creators_name: Massa, Andrea creators_name: Rocca, Paolo title: Improving the Effectiveness of GA-Based Approaches to Microwave Imaging through an Innovative Parabolic Crossover ispublished: inpress subjects: TU full_text_status: public abstract: Several studies have shown that evolutionary-based approaches are efficient, effective, and robust optimization methods for microwave imaging. However, the convergence rate of such techniques still does not meet all the requirements for on-line real applications and attempting to speed up the optimization is needed. In this paper, a new local search operator, the fitness-based parabolic crossover, is proposed and embedded into a real-coded genetic algorithm. Such a modification enables the imaging method to achieve a better trade-off between convergence rate and robustness to false solutions. By exploiting the relationship between the crossover operation and the local quadratic behavior of the functional, it is possible to increase the convergence rate of the genetic algorithm and thereby to obtain an acceptable solution with a smaller number of fitness function evaluations. The effectiveness of the modified genetic-algorithm-based imaging method is assessed by considering some synthetic test cases different in dimensions and noisy conditions. The obtained numerical results provide an empirical evidence of the efficiency and reliability of the proposed modified evolutionary algorithm. date: 2004-10 date_type: published institution: University of Trento department: informaticat refereed: FALSE referencetext: 1. J. H. Holland, Adaptation in Natural and Artificial System, 1975 :MIT Press 2. D. E. Goldberg, Genetic Algorithms in Search, Optimization and Machine Learning, 1989 :Addison-Wesley 3. A. Massa, "Genetic algorithm (GA) based techniques for 2D microwave inverse scattering", Recent Research Developments in Microwave Theory and Techniques, pp.193 -218 2002 :Transworld Research Network Press 4. S. Caorsi, A. Massa, and M. Pastorino, "A computational technique based on a real-coded genetic algorithm for microwave imaging purposes", IEEE Trans. Geosci. Remote Sens., vol. 38, no. 4, pp.1697 -1708 2000 5. M. Pastorino, A. Massa, and S. Caorsi, "A microwave inverse scattering technique for image reconstruction based on a genetic algorithm", IEEE Trans. Instrum. Meas., vol. 49, no. 3, pp.573 -578 2000 6. Z. Q. Meng, T. Takenaka, and T. Tanaka, "Image reconstruction of two-dimensional impenetrable objects using genetic algorithm", J. Electron. Waves Applicat., vol. 13, pp.95 -118 1999 7. H. K. Choi, S. K. Park, and J. W. Ra, "Reconstruction of a high-contrast penetrable object in pulsed time domain by using the genetic algorithm", Proc. IEEE Int. Geosci. Remote Sens. Symp., pp.136 -138 1997 8. A. Massa, M. Donelli, S. Caorsi, and M. Raffetto, "Parallel GA-based approach for microwave imaging applications", IEEE Trans. Antennas Propag., 9. R. L. Haupt and S. E. Haupt, Practical Genetic Algorithms, 1998 :Wiley 10. L. Davis, "Adapting operators probabilities in genetic algorithms", Proc. 3rd Int. Conf. Genetic Algorithms, pp.61 -69 1989 11. Z. Michalewicz, Genetic Algorithms + Data Structures + Evolution Programs, 1996 :Springer Verlag 12. T. Baeck and A. E. Eiben, "Empirical investigation of multiparent recombination operators in evolution strategies", Evolutionary Computation, vol. 5, pp.347 -365 1997 13. T. Stidsen, O. Caprani, and Z. Michalewicz, "A parabolic operator for parameter optimization problems", Proc. Congr. Evolutionary Computation, vol. 2, pp.1494 -1500 1999 14. D. S. Jones, The Theory of the Electromagnetism, 1964 :Pergamon 15. Y. Rahmat-Samii and E. Michielssen, Electromagnetic Optimization by Genetic Algorithms, 1999 :Wiley 16. S. Caorsi, G. L. Gragnani, and M. Pastorino, "An electromagnetic imaging approach using a multi-illumination technique", IEEE Trans. Biomed. Eng., vol. 41, no. 4, pp.406 -409 1994 17. J. H. Richmond, "Scattering by a dielectric cylinder of arbitrary cross section shape", IEEE Trans. Antennas Propag., vol. 13, no. 3, pp.334 -341 1965 18. D. S. Weile and E. Michielssen, "Genetic algorithm optimization applied to electromagnetics: A review", IEEE Trans. Antennas Propag., vol. 45, no. 3, pp.343 -353 1997 citation: Bort, Emmanuele and Massa, Andrea and Rocca, Paolo (2004) Improving the Effectiveness of GA-Based Approaches to Microwave Imaging through an Innovative Parabolic Crossover. [Technical Report] (In Press) document_url: http://www.eledia.org/students-reports/563/1/DIT-04-096.pdf