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