A greedy genetic algorithm for continuous variables electromagnetic optimization problems

Author

Fanni, Alessandra ; Marchesi, Michele ; Serri, Antonino ; Usai, Mariangela

Author_Institution

Dipartimento di Ingegneria Elettrica ed Elettronica, Cagliari, Italy

Volume

33

Issue

2

fYear

1997

fDate

3/1/1997 12:00:00 AM

Firstpage

1900

Lastpage

1903

Abstract

A greedy genetic algorithm for continuous variables electromagnetic optimization problems is presented. The presented algorithm is characterized by the use of a nonlinear simplex method as a principal optimizer, and of a greedy genetic algorithm to explore the search space, realizing a balance between diversity and a bias toward fitter individuals. The resulting algorithm merges the efficiency typical of calculus-based search with the robustness typical of random methods. A detailed comparison of the performance obtained implementing several strategies is presented, using an electromagnetic design test problem

Keywords

electrical engineering; electrical engineering computing; electromagnetism; genetic algorithms; magnetic resonance; parallel algorithms; random processes; search problems; MRI system; calculus-based search; continuous variables electromagnetic optimization; diversity; efficiency; electromagnetic design test problem; greedy genetic algorithm; nonlinear simplex method; performance comparison; random methods; robustness; search space; Design optimization; Genetic algorithms; Magnetosphere; Merging; Optimization methods; Performance evaluation; Robustness; Simulated annealing; Space exploration; Testing;

fLanguage

English

Journal_Title

Magnetics, IEEE Transactions on

Publisher

ieee

ISSN

0018-9464

Type

jour

DOI

10.1109/20.582659

Filename

582659