Title :
A Multi-Objective Endocrine PSO Algorithm
Author :
Chen De-bao ; Zou Feng
Author_Institution :
Dept. of Phys. & Electron. Inf., Huaibei Coal Ind. Teachers´ Coll., Huaibei, China
Abstract :
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.
Keywords :
particle swarm optimisation; endocrine system; multi-objective endocrine PSO Algorithm; particle swarm optimization; stimulation hormones; Constraint optimization; Control systems; Educational institutions; Endocrine system; Evolutionary computation; Fuel processing industries; Industrial electronics; Information science; Particle swarm optimization; Physics;
Conference_Titel :
Information Science and Engineering (ICISE), 2009 1st International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-4909-5
DOI :
10.1109/ICISE.2009.76