DocumentCode :
7488
Title :
A Parallel Version of the Self-Adaptive Low-High Evaluation Evolutionary-Algorithm for Electromagnetic Device Optimization
Author :
Dilettoso, Emanuele ; Rizzo, Santi Agatino ; Salerno, Nunzio
Author_Institution :
Dipt. di Ing. Elettr., Elettron. e Inf., Univ. of Catania, Catania, Italy
Volume :
50
Issue :
2
fYear :
2014
fDate :
Feb. 2014
Firstpage :
633
Lastpage :
636
Abstract :
The self-adaptive low-high evaluation evolutionary-algorithm (SALHE-EA) is used to solve multimodal optimization problems. SALHE-EA is able to find the multiple optima of a single objective function (OF) and to give an idea of the fitness landscape in the neighborhood of these optima. This aspect is of crucial importance when the single OF is obtained using the weighted sum of the OFs, each related to a different goal of the optimization problem. This paper presents an improved version of SALHE-EA. This new version has several new features and, mainly, the suitability for parallelization.
Keywords :
electromagnetic devices; evolutionary computation; OF; SALHE-EA; electromagnetic device optimization; fitness landscape; multimodal optimization problems; multiple optima; parallel self-adaptive low-high evaluation evolutionary-algorithm; single objective function; Electromagnetic devices; Electromagnetic heating; Finite element analysis; Optimization; Sociology; Statistics; Wheels; Evolutionary computation; finite element methods (FEMs); induction heating; optimization methods; parallel algorithms;
fLanguage :
English
Journal_Title :
Magnetics, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9464
Type :
jour
DOI :
10.1109/TMAG.2013.2284928
Filename :
6749031
Link To Document :
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