Magnetic particle swarm optimization with estimation of distribution

Author

Prampero, Paulo S. ; Attux, Romis

Author_Institution

Fed. Inst. of Sci., Technol. & Educ. of Sao Paulo, Salto, Brazil

fYear

2011

fDate

5-8 June 2011

Firstpage

1994

Lastpage

2001

Abstract

The magnetic particle swarm (MPS) algorithm is an approach based on the phenomenon dipole repulsion by a magnetic field. In this paper, a new version of this algorithm, which employs an estimation of distribution step as an additional search heuristic, is proposed and applied to seven well-known test functions for 30-dimensional, 120-dimensional and 1000 dimensional search spaces. The performance of the new approach is compared to that of benchmark differential evolution and estimation of distribution methods, and the results reveal its potential in terms of multimodal search in the context of complex optimization tasks.

Keywords

evolutionary computation; magnetic fields; magnetic moments; particle swarm optimisation; benchmark differential evolution; complex optimization task context; distribution method estimation; distribution step estimation; magnetic field; magnetic particle swarm optimization; multimodal search; phenomenon dipole repulsion; search heuristic; search space; test function; Context; Cost function; Estimation; Magnetic particles; Particle swarm optimization; Probabilistic logic; differential evolution; estimation of distribution algorithms; global search methods; magnetic particle swarm; particle swarm optimization;

fLanguage

English

Publisher

ieee

Conference_Titel

Evolutionary Computation (CEC), 2011 IEEE Congress on

Conference_Location

New Orleans, LA

ISSN

Pending

Print_ISBN

978-1-4244-7834-7

Type

conf

DOI

10.1109/CEC.2011.5949860

Filename

5949860