Engineering optimization with particle swarm

被引：236

作者：

Hu, XH ^{[1
]}

Eberhart, RC ^{[1
]}

Shi, YH ^{[1
]}

机构：

[1] Purdue Univ, Dept Biomed Engn, W Lafayette, IN 47907 USA

来源：

PROCEEDINGS OF THE 2003 IEEE SWARM INTELLIGENCE SYMPOSIUM (SIS 03) | 2003年

关键词：

D O I：

10.1109/SIS.2003.1202247

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents a modified particle swarm optimization (PSO) algorithm for engineering optimization problems with constraints. PSO is started with a group of feasible solutions and a feasibility function is used to check if the newly explored solutions satisfy all the constraints. All the particles keep only those feasible solutions in their memory. Several engineering design optimization problems were tested and the results show that PSO is an efficient and general approach to solve most nonlinear optimization problems with inequity constraints.

引用

页码：53 / 57

页数：5

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