DESIGN OPTIMIZATION OF POWER OBJECTS BASED ON CONSTRAINED NON-LINEAR MINIMIZATION, GENETIC ALGORITHMS, PARTICLE SWARM OPTIMIZATION ALGORITHMS AND DIFFERENTIAL EVOLUTION ALGORITHMS

被引：0

作者：

Salkoski, Rasim ^{[1
]}

Chorbev, Ivan ^{[2
]}

机构：

[1] Univ Informat Sci & Technol, Ohrid, Macedonia

[2] Univ Ss Cyril & Methodius, Fac Comp Sci & Engn, Skopje, Macedonia

来源：

INTERNATIONAL JOURNAL ON INFORMATION TECHNOLOGIES AND SECURITY | 2014年 / 6卷 / 03期

关键词：

Constrained non-linear minimization; Genetic Algorithms; Particle Swarm Optimization; Differential Evolution; Arc Suppression Coil;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper gives a detailed comparative analysis of Constrained non-linear minimization (CN), Genetic Algorithms (GA), Particle Swarm Optimization Algorithms (PSO) and Differential Evolution Algorithms (DE) results. The Objective Function that is optimized is a minimization dependent and all constraints are normalized and modeled as inequalities. The results demonstrate the potential of the DE Algorithm, shows its effectiveness and robustness to solve the optimal power object.

引用

页码：21 / 30

页数：10

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