DocumentCode :
1177078
Title :
Electromagnetic Optimization Using a Cultural Self-Organizing Migrating Algorithm Approach Based on Normative Knowledge
Author :
Coelho, Leandro Dos Santos ; Alotto, Piergiorgio
Author_Institution :
Autom. & Syst. Lab., Pontifical Catholic Univ. of Parana, Curitiba
Volume :
45
Issue :
3
fYear :
2009
fDate :
3/1/2009 12:00:00 AM
Firstpage :
1446
Lastpage :
1449
Abstract :
A new class of stochastic optimization algorithms called the self-organizing migrating algorithm (SOMA) has recently been proposed. SOMA works on a population of potential solutions called specimen and is based on the self-organizing behavior of groups of individuals in a ldquosocial environment.rdquo This paper introduces a modified SOMA approach based on an operator featuring normative knowledge, a characteristic of cultural algorithms. The efficiency of the proposed method is tested on Loney´s solenoid design.
Keywords :
computational electromagnetics; evolutionary computation; optimisation; self-adjusting systems; solenoids; Loney´s solenoid design; cultural self-organizing migrating algorithm; electromagnetic optimization; modified SOMA approach; normative knowledge; operator; social environment; stochastic optimization algorithms; Cultural algorithm; Loney´s solenoid design; electromagnetic optimization; self-organizing migrating algorithm (SOMA);
fLanguage :
English
Journal_Title :
Magnetics, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9464
Type :
jour
DOI :
10.1109/TMAG.2009.2012668
Filename :
4787410
Link To Document :
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