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Elitist Genetic Algorithm Performance on the Uniform Circular Antenna Array Pattern Synthesis Problem

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PL
Synteza kołowej anteny matrycowej z wykorzystaniem algorytmu genetycznego
Języki publikacji
EN
Abstrakty
EN
In this paper, the impacts of elitism rate on the Genetic Algorithm (GA) performance for the Uniform Circular Antenna Array Pattern Synthesis Problem are investigated. For this purpose, a circular antenna array with uniformly spaced isotropic elements having identical excitation amplitudes is used as a model. Unlike the classical GA, we use a GA structure having an elitist population update approach for improved GA performance. In the elitist approach, a certain ratio of the population (i.e. the fittest individuals) is directly transferred to the next generation.
PL
W artykule zaprezentowano wykorzystanie algorytmu genetycznego do analizy jednorodnej kołowej matrycy anten. W tym celu jako model użyto anteny z regularnie rozmieszczonymi elementami mającymi tę samą amplitudę pobudzania. Użyto zmodyfikowanego algorytmu genetycznego z populacją elistyczną.
Rocznik
Strony
273--277
Opis fizyczny
Bibliogr. 20 poz., tab., wykr.
Twórcy
autor
autor
Bibliografia
  • [1] Holland, J., Adaptation in Natural and Artificial Systems, University of Michigan Press, 1975
  • [2] Goldberg, D.E., Genetic Algorithms in Search Optimization and Machine Learning, Addison–Wesley Longman, 1989.
  • [3] Michalewi cz , Z. , Genetic Algorithms + Data Structures = Evolution Programs, Springer-Verlag, 1992
  • [4] Whitley, L.D., Foundations of Genetic Algorithms-2, Morgan Kaufmann Publishers Inc., 1993
  • [5] Balanis, C.A., Antenna Theory Analysis and Design, John Wiley & Inderscience Publications, 2005
  • [6] Visser , H.J., Array and Phased Array Antenna Basics, John Wiley & Sons Publications, 2005
  • [7] Panduro, M.A., Mendez, A.L., Dominguez, R., Romero, G, Design of Non-uniform Circular Antenna Arrays for Side Lobe Reduction Using the Method of Genetic Algorithms, AEÜ - International Journal of Electronics and Communications, 60 (2006), 713-717
  • [8] Shihab, M., Najjar, Y., Dib, N., Khodier, M., Design of Non Uniform Circular Antenna Arrays Using Particle Swarm Optimization, Journal of Electrical Engineering, 59 (2008), no. 4, 216-220
  • [9] Xu, Z., Li , H., Liu, Q. - Z., Pattern Synthesis of Conformal Antenna Array by the Hybrid Genetic Algorithm, Progress in Electromagnetics Research (PIER), 79 (2008), 75–90
  • [10] Yaman, F. and Yilmaz, A.E., Impacts of Genetic Algorithm Parameters on the Solution Performance for the Uniform Circular Antenna Array Pattern Synthesis Problem, Journal of Applied Research and Technology, Vol.8 (2010), No.3, 378-394
  • [11] Liang, Y. and Leung, K.-S., Genetic Algorithm with Adaptive Elitist-Population Strategies for Multimodal Function Optimization, Applied Soft Computing, 11 (2011), 2017-2034
  • [12] Jayaram, M.A., Nataraja, M.C. and Ravikumar, C.N., Elitist Genetic Algorithm Models:Optimization of High Performance Concrete Mixes, Materials and Manufacturing Processes, 24 (2009), 225-229
  • [13] Kim, J. -L., Permutation-Based Elitist Genetic Algorithm Using Serial Scheme for Large-Sized Resource-Constrained Project Scheduling, Proceedings of the 2007 Winter Simulation Conference, 2007, 2112-2118
  • [14] Al Jadaan, O., Rajamani, L., Rao, C.R., Non- Dominated Ranked Genetic Algorithm for Solving Multi-Objective Optimization Problems: NRGA, Journal of Theoretical and Applied Information Technology, 2008, 60-67
  • [15] Ahn, C.W. and Ramakrishna, R.S., Elitism-Based Compact Genetic Algorithms, IEEE Transactions on Evolutionary Computation, Vol. 7, No. 4, (2003), 367-385
  • [16] Leung, K.-S. and Liang, Y., Adaptive Elitist-Population Based Genetic Algorithm for Multimodal Function Optimization, Springer-Verlag Berlin Heidelberg, GECCO (2003), 1160-1171
  • [17] Lozano, M., Herrera, F., Cano, J.R., Replacement Strategies to Preserve Useful Diversity in Steady-State Genetic Algorithms, Information Sciences, 178 (2008), 4421–4433
  • [18] Kim, J. -L. , Examining the Relationship Between Algorithm Stopping Criteria and Performance Using Elitist Genetic Algorithm, Proceedings of the 2010 Winter Simulation Conference, (2010), 3220-3227
  • [19] Liu, M. and He, J., Automated Analog Circuit Design Synthesis Using a Hybrid Genetic Algorithm with Hyper-Mutation and Elitist Strategies, International Journal of Information Technology and Computer Science, 1 (2009), 23-32
  • [20] Tang, Z., Zhu, Y., Wei, G., Zhu, J., An Elitist Selection Adaptive Genetic Algorithm for Resource Allocation in Multiuser Packet-based OFDM Systems, Journal of Communications, Vol. 3, No. 3 (2008), 27-32
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPOB-0049-0061
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