Differentiated Meta-PSO Methods for Array Optimization
The particle swarm optimization (PSO) method has been successfully applied to different electromagnetic optimization problems. Because of the complexity of this kind of problems, the associated cost function is in general computationally expensive. A fast convergence of the optimization algorithm is...
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| Published in | IEEE transactions on antennas and propagation Vol. 56; no. 1; pp. 67 - 75 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
New York, NY
IEEE
01.01.2008
Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0018-926X 1558-2221 |
| DOI | 10.1109/TAP.2007.912942 |
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| Abstract | The particle swarm optimization (PSO) method has been successfully applied to different electromagnetic optimization problems. Because of the complexity of this kind of problems, the associated cost function is in general computationally expensive. A fast convergence of the optimization algorithm is hence required to attain results in short time. Here few variations over the standard algorithm, referred to as differentiated meta-PSO, aimed to enhance the global search capability, and to improve the algorithm convergence, are introduced. In order to verify their effectiveness the different techniques have been first applied to benchmark test functions and then used for the optimization of a planar array. |
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| AbstractList | The particle swarm optimization (PSO) method has been successfully applied to different electromagnetic optimization problems. Because of the complexity of this kind of problems, the associated cost function is in general computationally expensive. A fast convergence of the optimization algorithm is hence required to attain results in short time. Here few variations over the standard algorithm, referred to as differentiated meta-PSO, aimed to enhance the global search capability, and to improve the algorithm convergence, are introduced. In order to verify their effectiveness the different techniques have been first applied to benchmark test functions and then used for the optimization of a planar array. |
| Author | Zich, R.E. Pirinoli, P. Matekovits, L. Selleri, S. Mussetta, M. |
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| Keywords | Performance evaluation particle swarm Electromagnetism Algorithm performance Evolutionary computation Convergence rate Cost function Swarm intelligence Planar antenna arrays Arrays Algorithm Optimization |
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| References | ref12 shi (ref23) 2002; 2 ref15 ref14 ref31 ref11 ref2 ref1 ref17 rahmat-samii (ref6) 1999 kennedy (ref10) 2001 ref16 ref19 ref18 hodgson (ref13) 2002 goldberg (ref4) 1989 ref24 ref26 ref25 ref20 ref21 davis (ref3) 1987 ref28 ref27 ref8 ref7 ref9 ref5 kennedy (ref22) 1999; 3 tseng (ref30) 1968; 56 eberhart (ref29) 2001 |
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| SubjectTerms | Algorithms Antennas Applied classical electromagnetism Applied sciences Arrays Benchmark testing Benchmarking Convergence Cost function Design optimization Electromagnetic wave propagation, radiowave propagation Electromagnetism; electron and ion optics Evolutionary computation Exact sciences and technology Fundamental areas of phenomenology (including applications) Mathematical analysis Microwave antennas Optimization Optimization methods particle swarm Particle swarm optimization Physics Planar arrays Radiocommunications Stochastic processes Telecommunications Telecommunications and information theory |
| Title | Differentiated Meta-PSO Methods for Array Optimization |
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