Engineering optimization with particle swarm

Author

Hu, Xiaohui ; Eberhart, Russell C. ; Shi, Yuhui

Author_Institution

Dept. of Biomed. Eng., Purdue Univ., West Lafayette, IN, USA

fYear

2003

fDate

24-26 April 2003

Firstpage

53

Lastpage

57

Abstract

The 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.

Keywords

constraint theory; engineering computing; evolutionary computation; nonlinear programming; search problems; PSO algorithm; constraint satisfaction; engineering optimization; feasibility function; inequity constraints; modified particle swarm optimization; nonlinear optimization problems; Biomedical engineering; Constraint optimization; Design engineering; Design optimization; Equations; Evolutionary computation; Particle swarm optimization; Power line communications; Stochastic processes; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Swarm Intelligence Symposium, 2003. SIS '03. Proceedings of the 2003 IEEE

Print_ISBN

0-7803-7914-4

Type

conf

DOI

10.1109/SIS.2003.1202247

Filename

1202247