The Significance of Genetic Representation in Genetic Antenna Design

Abstract

Genetic algorithms have been shown to be effective in the design of small antennas. However, their effectiveness depends on both the mechanisms of the genetic algorithm and the genetic representation of the problem. Here we present three genetic chromosome representations for a small antenna design problem (lowest VSWR for a specified h/lambda cube size) and compare the results of the three optimization processes. Our work shows that different chromosome representations lead to solutions in different, overlapping subclasses, and that an important consideration in genetic antenna design is finding a simple chromosome representation which is capable of representing the subclass containing the "optimal" solution. Our initial results show that the chromosome design itself is an important factor in successful genetic antenna design.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2003
Accession Number
ADA418160

Entities

People

  • Edward E. Altshuler
  • Steven R. Best
  • Terry H. O'donnell

Organizations

  • Air Force Research Laboratory

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Algorithms
  • Antenna Configurations
  • Antennas
  • Chromosomes
  • Coding
  • Electrically Small Antennas
  • Elevation
  • Frequency
  • Genetic Algorithms
  • Military Research
  • Scientific Research

Fields of Study

  • Engineering

Readers

  • Computer Vision.
  • Electromagnetic Wave Scattering and Antenna Radiation Engineering
  • Operations Research

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms
  • Biotechnology