Magnetic Particle Swarm Optimization with Estimation of Distribution

被引：0
|
作者：
Prampero, Paulo S. [1 ,2 ]
Attux, Romis [2 ]
机构：
[1] Fed Inst Sci Technol & Educ Sao Paulo, Campus Salto, Salto, Brazil
[2] FEEC Univ Campinas, Dept Comp Engn & Ind Automat, Campinas, Brazil
来源：
2011 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC) | 2011年
关键词：
particle swarm optimization; magnetic particle swarm; global search methods; differential evolution; estimation of distribution algorithms;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
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.
引用
收藏
页码：1994 / 2001
页数：8
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