A Multi-Objective Endocrine PSO Algorithm

A novel endocrine particle swarm optimization algorithm (EPSO) base on the idea of general PSO algorithm and endocrine is proposed in the paper. In the method, particles are grouped by stimulation hormones (SH) of endocrine system, and the best positions of classes are used to update the positions o...

Full description

Saved in:
Bibliographic Details
Published in2009 First International Conference on Information Science and Engineering pp. 3567 - 3570
Main Authors Chen, De-bao, Zou, Feng
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2009
Subjects
Constraint optimization
Control systems
Educational institutions
Endocrine system
Evolutionary computation
Fuel processing industries
Industrial electronics
Information science
Particle swarm optimization
Physics
Online AccessGet full text
ISBN142444909X
9781424449095
ISSN2160-1283
DOI10.1109/ICISE.2009.76

Cover

More Information
Summary:A novel endocrine particle swarm optimization algorithm (EPSO) base on the idea of general PSO algorithm and endocrine is proposed in the paper. In the method, particles are grouped by stimulation hormones (SH) of endocrine system, and the best positions of classes are used to update the positions of particles which controlled by them. The new positions of particles are not only determined by the best position which it achieved so far and the global best position in current generation, but also influenced by the best position of class which is belonged to the global information and local information are combined completely. The simulation experiments with three typical multi-objective functions are used to indicate the effectiveness of the method with compared to MOPSO-DC.
ISBN:142444909X
9781424449095
ISSN:2160-1283
DOI:10.1109/ICISE.2009.76