Hill Valley Function Based Niching Particle Swarm Optimization for Multimodal Functions

被引：4
|
作者：
Wang, Junnian [1 ]
Liu, Deshun [1 ]
Shang, Helen [2 ]
机构：
[1] Hunan Univ Sci & Technol, Coll Hunan Prov, Knowledge Proc & Networked Mfg Key Lab, Xiangtan 411201, Peoples R China
[2] Laurentian Univ, Sch Engn, Sudbury, ON P3E 2C6, Canada
来源：
2009 INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND COMPUTATIONAL INTELLIGENCE, VOL I, PROCEEDINGS | 2009年
基金：
美国国家科学基金会;
关键词：
particle swarm; niching; Hill Valley Function;
D O I：
10.1109/AICI.2009.250
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A novel niching Particle Swarm Optimization (PSO) method based on a hill valley function is proposed. In this algorithm, the hill valley function is used to decide whether the niching seed particle and its neighbour are on the same hill, and if they are, a new niching is formed. The hill valley function is also used to decide whether two niching subswarms are on the same hill, and if they are, the two niching subswarms are merged. The proposed algorithm is evaluated using three benchmark test functions. Results indicate that the proposed hill valley function based niching PSO algorithm has strong adaptive searching capability and efficient convergence in searching multiple solutions.
引用
收藏
页码：139 / +
页数：2
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