Parallel Adaptive Immune Quantum-Behaved Particle Swarm Optimization Algorithm (PAIQPSO)

Author

Liu Jun-hui ; Li Na

Author_Institution

Dept. of Inf. Eng., Zhengzhou Coll. of Animal Husbandry Eng., Zhengzhou, China

fYear

2012

Firstpage

435

Lastpage

438

Abstract

In order to escape from premature convergence and lack good direction in particles the evolutionary process, quantum technology and immunologic mechanism were employed, and an adaptive immune quantum-behaved particle swarm optimization algorithm was provided. Meanwhile, according to larger calculation and longer consumed time, parallel computation technology was introduced into the provided algorithm too. Simulation experiments show that the presented particle algorithm has better performance.

Keywords

evolutionary computation; particle swarm optimisation; evolutionary process; immunologic mechanism; parallel adaptive immune quantum-behaved algorithm; parallel computation technology; particle swarm optimization algorithm; premature convergence; quantum technology; Algorithm design and analysis; Computational efficiency; Convergence; Optimization; Parallel algorithms; Particle swarm optimization; Vaccines; immunologic mechanism; parallel computation; particle swarm optimization; quantum technology;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent System Design and Engineering Application (ISDEA), 2012 Second International Conference on

Conference_Location

Sanya, Hainan

Print_ISBN

978-1-4577-2120-5

Type

conf

DOI

10.1109/ISdea.2012.478

Filename

6173239