Title :
An improved quantum-behaved Particle Swarm Optimization using fitness-weighted preferential recombination
Author :
Pat, Ankit ; Hota, Ashish Ranjan
Author_Institution :
Dept. of Math., Indian Inst. of Technol., Kharagpur, India
Abstract :
Quantum-behaved particle swarm optimization (QPSO) is a widely used algorithm for global optimization of multi-dimensional functions. In this paper, a modified and improved QPSO using fitness weighted recombination operator along with a fitness proportionate selection mechanism is proposed. The proposed algorithm is tested on different benchmark functions and compared with the standard Particle Swarm Optimization (PSO) and QPSO. The experimental results show comprehensive superiority of the proposed algorithm.
Keywords :
particle swarm optimisation; fitness proportionate selection mechanism; fitness-weighted preferential recombination; quantum-behaved particle swarm optimization; Optimization; global optimization; quantum computing; quantum-behaved particle swarm optimization; recombination operator;
Conference_Titel :
Nature and Biologically Inspired Computing (NaBIC), 2010 Second World Congress on
Conference_Location :
Fukuoka
Print_ISBN :
978-1-4244-7377-9
DOI :
10.1109/NABIC.2010.5716316
