Title :
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
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;
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
DOI :
10.1109/ISdea.2012.478
