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