QPSO-based algorithm for multi-objective optimization problem

被引：0
|
作者：
Guan, Fangjing [1 ]
Xu, Wenbo [1 ]
Sun, Jun [1 ]
机构：
[1] So Yangtze Univ, Comp Engn Sch Informat Technol, Jiangsu 214122, Peoples R China
来源：
DCABES 2006 PROCEEDINGS, VOLS 1 AND 2 | 2006年
关键词：
particle swarm optimization; multi-objective optimization; quantum-behaved particle swarm optimization;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Quantum-behaved Particle Swarm Optimization Algorithm is a global convergent optimization algorithm. In this paper, we propose a Vector Evaluated Quantum-behaved Particle Swarm Optimization algorithm (VEQPSO) to solve multi-objective optimization problem. After described the concepts of VEQPSO, we test it on rnulti-objective benchmark problems. The experiment results of VEQPSO on four classic multi-objective minimization functions show the efficiency of the algorithm for solving multi-objective optimization problem.
引用
收藏
页码：1298 / 1302
页数：5
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