An improved Particle Swarm Optimization algorithm with rank-based selection

被引：4
|
作者：
Wan, Li-Yong [1 ]
Li, Wei [1 ]
机构：
[1] Wuhan Univ Sci & Engn, Coll Humanity & Social Sci, Wuhan 430073, Peoples R China
来源：
PROCEEDINGS OF 2008 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7 | 2008年
关键词：
Particle Swarm Optimization; rank-based selection; function optimization;
D O I：
10.1109/ICMLC.2008.4621118
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Particle Swarm Optimization (PSO) is a population-based, self adaptive search optimization technique that has been applied to rind optimal or near-optimal solutions for real-world optimization problems. In this paper, rank-based selection is proposed for the particle swarm optimizer. The method applies rank-based selection to replace half of the lower fitness population with the higher fitness population of the swarm. Performance is compared with some other methods using the benchmark function.
引用
收藏
页码：4090 / +
页数：2
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