An improved quantum-behaved particle swarm optimization algorithm

Authors:
Jie Yang;Jiahua Xie
Affiliations:
School of Computer and Information, Shanghai Second Polytechnic University, Shanghai, China;School of Computer and Information, Shanghai Second Polytechnic University, Shanghai, China
Venue:
CAR'10 Proceedings of the 2nd international Asia conference on Informatics in control, automation and robotics - Volume 2
Year:
2010

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Abstract

Quantum-behaved particle swarm optimization (QPSO) algorithm is a global convergence guaranteed algorithm, which shows good search ability in many optimization problems. In this paper, we present an improved QPSO algorithm, called IQPSO, by combining QPSO and an opposition-based learning concept. Experimental studies on four well-known benchmark problems show that IQPSO achieves better results than QPSO and other variants of PSO on majority of test problems.