Advances in Particle Swarm Optimization for Antenna Designs: Real-Number, Binary, Single-Objective and Multiobjective Implementations

The particle swarm optimization (PSO) is a recently developed evolutionary algorithm (EA) based on the swarm behavior in the nature. This paper presents recent advances in applying a versatile PSO engine to real-number, binary, single-objective and multiobjective optimizations for antenna designs, w...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on antennas and propagation Jg. 55; H. 3; S. 556 - 567
Hauptverfasser: Nanbo Jin, Rahmat-Samii, Y.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York, NY IEEE 01.03.2007
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithm design and analysis
Algorithms
Antenna arrays
Antenna measurements
Antennas
Aperiodic antenna array
Applied classical electromagnetism
Applied sciences
binary optimization
Design optimization
Electromagnetic wave propagation, radiowave propagation
Electromagnetism; electron and ion optics
Engines
Evolutionary computation
Exact sciences and technology
Flowcharts
Fundamental areas of phenomenology (including applications)
multiobjective
Optimization methods
Particle swarm optimization
particle swarm optimization (PSO)
Physics
Radiocommunications
real-number optimization
Reflector antennas
single-objective
Studies
Telecommunications
Telecommunications and information theory
Performance evaluation
Lateral lobe
single-objective
Electromagnetism
Evolutionary algorithm
Evolutionary computation
Multiobjective programming
optimization methods
Binary number
Implementation
Aperiodic array antenna
Aperiodic antenna array
Biomimetics
real-number optimization
binary optimization
multiobjective
Swarm intelligence
particle swarm optimization (PSO)
Antenna array
ISSN:0018-926X, 1558-2221
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:The particle swarm optimization (PSO) is a recently developed evolutionary algorithm (EA) based on the swarm behavior in the nature. This paper presents recent advances in applying a versatile PSO engine to real-number, binary, single-objective and multiobjective optimizations for antenna designs, with a randomized Newtonian mechanics model developed to describe the swarm behavior. The design of aperiodic (nonuniform and thinned) antenna arrays is presented as an example for the application of the PSO engine. In particular, in order to achieve an improved peak sidelobe level (SLL), element positions in a nonuniform array are optimized by real-number PSO (RPSO). On the other hand, in a thinned array, the on/off state of each element is determined by binary PSO (BPSO). Optimizations for both nonuniform arrays and thinned arrays are also expanded to multiobjective cases. As a result, nondominated designs on the Pareto front enable one to achieve other design factors than the peak SLL. Optimized antenna arrays are compared with periodic arrays and previously presented aperiodic arrays. Selected designs fabricated and measured to validate the effectiveness of PSO in practical electromagnetic problems
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ObjectType-Article-2
ObjectType-Feature-1
ISSN:0018-926X
1558-2221
DOI:10.1109/TAP.2007.891552