An Improved Quantum-Behaved Particle Swarm Optimization Algorithm

被引：5

作者：

Yang, Jie ^{[1
]}

Xie, Jiahua ^{[1
]}

机构：

[1] Shanghai Second Polytech Univ, Sch Comp & Informat, Shanghai, Peoples R China

来源：

2010 2ND INTERNATIONAL ASIA CONFERENCE ON INFORMATICS IN CONTROL, AUTOMATION AND ROBOTICS (CAR 2010), VOL 2 | 2010年

关键词：

particle swarm optimization (PSO); quantum; evolutionary computation; optimization;

D O I：

10.1109/CAR.2010.5456744

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：159 / 162

页数：4

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