By Topic

Antenna Design With a Mixed Integer Genetic Algorithm

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Randy L. Haupt ; Appl. Res. Lab., Pennsylvania State Univ., State College, PA

Antenna design variables, such as size, have continuous values while others, such as permittivity, have a finite number of values. Having both variable types in one problem requires a mixed integer optimization algorithm. This paper describes a genetic algorithm (GA) that works with real and/or binary values in the same chromosome. The algorithm is demonstrated on designing low side-lobe phase tapers, circularly polarized patch antennas, and identically thinned subarrays

Published in:

IEEE Transactions on Antennas and Propagation  (Volume:55 ,  Issue: 3 )