Modified Social-Spider Optimization Algorithm Applied to Electromagnetic Optimization

被引：43

作者：

Klein, Carlos E. ^{[1
]}

Segundo, Emerson H. V. ^{[2
]}

Mariani, Viviana C. ^{[2
,3
]}

Coelho, Leandro dos S. ^{[1
,3
]}

机构：

[1] Pontificia Univ Catolica Parana, Posgrad Engn Prod & Sistemas, BR-80215901 Curitiba, Parana, Brazil

[2] Pontificia Univ Catolica Parana, Posgrad Engn Mecan, BR-80215901 Curitiba, Parana, Brazil

[3] Univ Fed Parana, Dept Engn Elet, BR-83255976 Curitiba, Parana, Brazil

来源：

IEEE TRANSACTIONS ON MAGNETICS | 2016年 / 52卷 / 03期

关键词：

Electromagnetic optimization; metaheuristics; natural gradient (NG); social-spider optimization (SSO); SWARM OPTIMIZATION;

D O I：

10.1109/TMAG.2015.2483059

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：

Social-spider optimization (SSO) is a new nature-inspired algorithm of the swarm intelligence field to global optimization applications, which is based on the simulation of cooperative behavior of social spiders. To enhance the performance of the standard SSO, a modified SSO (MSSO) approach based on beta distribution and natural gradient local search was proposed in this paper. In order to verify the performance of the MSSO, tests using Loney's solenoid benchmark and a brushless direct current motor benchmark are realized comparing the effectiveness of the SSO and the proposed MSSO. The results of this paper demonstrated that the MSSO performance is promising in electromagnetics optimization.

引用

页数：4

共 15 条

[1] Synthesis of the β-distribution as an aid to stochastic global optimization [J].

Ali, M. M. .

COMPUTATIONAL STATISTICS & DATA ANALYSIS, 2007, 52 (01) :133-149

[2] Natural gradient works efficiently in learning [J].

Amari, S .

NEURAL COMPUTATION, 1998, 10 (02) :251-276

[3]

[Anonymous], 2013, Evolutionary Optimization Algorithms

[4] Use of intelligent-particle swarm optimization in electromagnetics [J].

Ciuprina, G ;

Ioan, D ;

Munteanu, I .

IEEE TRANSACTIONS ON MAGNETICS, 2002, 38 (02) :1037-1040

[5] Gaussian Artificial Bee Colony Algorithm Approach Applied to Loney's Solenoid Benchmark Problem [J].

Coelho, Leandro dos Santos ;

Alotto, Piergiorgio .

IEEE TRANSACTIONS ON MAGNETICS, 2011, 47 (05) :1326-1329

[6] Tribes Optimization Algorithm Applied to the Loney's Solenoid [J].

Coelho, Leandro Dos Santos ;

Alotto, Piergiorgio .

IEEE TRANSACTIONS ON MAGNETICS, 2009, 45 (03) :1526-1529

[7] Electromagnetic Optimization Using a Cultural Self-Organizing Migrating Algorithm Approach Based on Normative Knowledge [J].

Coelho, Leandro dos Santos ;

Alotto, Piergiorgio .

IEEE TRANSACTIONS ON MAGNETICS, 2009, 45 (03) :1446-1449

[8] A swarm optimization algorithm inspired in the behavior of the social-spider [J].

Cuevas, Erik ;

Cienfuegos, Miguel ;

Zaldivar, Daniel ;

Perez-Cisneros, Marco .

EXPERT SYSTEMS WITH APPLICATIONS, 2013, 40 (16) :6374-6384

[9]

DiBarba P, 1995, INT J APPL ELECTROM, V6, P247

[10] Completely derandomized self-adaptation in evolution strategies [J].

Hansen, N ;

Ostermeier, A .

EVOLUTIONARY COMPUTATION, 2001, 9 (02) :159-195

← 1 2 →