Self-Adaptive Differential Evolution Applied to Real-Valued Antenna and Microwave Design Problems

Particle swarm optimization (PSO) is an evolutionary algorithm based on the bird fly. Differential evolution (DE) is a vector population based stochastic optimization method. The fact that both algorithms can handle efficiently arbitrary optimization problems has made them popular for solving proble...

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Bibliographic Details
Published in:IEEE transactions on antennas and propagation Vol. 59; no. 4; pp. 1286 - 1298
Main Authors: Goudos, S K, Siakavara, K, Samaras, T, Vafiadis, E E, Sahalos, J N
Format: Journal Article
Language:English
Published: New York, NY IEEE 01.04.2011
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithm design and analysis
Algorithms
Antennas
Applied classical electromagnetism
Applied sciences
Arrays
Convergence
Differential evolution (DE)
Electromagnetic wave propagation, radiowave propagation
Electromagnetism; electron and ion optics
Evolution
evolutionary algorithms (EAs)
Exact sciences and technology
Fundamental areas of phenomenology (including applications)
linear array synthesis
Microstrip filters
Microwave antennas
microwave filter design
Microwave filters
Microwave imaging
Microwaves
Optimization
optimization methods
particle swarm optimization (PSO)
patch antenna design
Physics
Radiocommunications
Strategy
Studies
Telecommunications
Telecommunications and information theory
Performance evaluation
Electromagnetism
Adaptive algorithm
Evolutionary algorithm
Printed antenna
optimization methods
Stochastic method
microwave filter design
Adaptive method
Particle swarm optimization
linear array synthesis
patch antenna design
Biomimetics
Algorithm performance
evolutionary algorithms (EAs)
Differential evolution (DE)
Convergence rate
Linear antenna arrays
particle swarm optimization (PSO)
Antenna array
Antenna synthesis
ISSN:0018-926X, 1558-2221
Online Access:Get full text
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Summary:Particle swarm optimization (PSO) is an evolutionary algorithm based on the bird fly. Differential evolution (DE) is a vector population based stochastic optimization method. The fact that both algorithms can handle efficiently arbitrary optimization problems has made them popular for solving problems in electromagnetics. In this paper, we apply a design technique based on a self-adaptive DE (SADE) algorithm to real-valued antenna and microwave design problems. These include linear-array synthesis, patch-antenna design and microstrip filter design. The number of unknowns for the design problems varies from 6 to 60. We compare the self-adaptive DE strategy with popular PSO and DE variants. We evaluate the algorithms' performance regarding statistical results and convergence speed. The results obtained for different problems show that the DE algorithms outperform the PSO variants in terms of finding best optima. Thus, our results show the advantages of the SADE strategy and the DE in general. However, these results are considered to be indicative and do not generally apply to all optimization problems in electromagnetics.
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ISSN:0018-926X
1558-2221
DOI:10.1109/TAP.2011.2109678