A Symbiosis-based Artificial Fish Swarm Algorithm

被引：0
|
作者：
Liu, Qing [1 ]
Odaka, Tomohiro [1 ]
Kuroiwa, Jousuke [1 ]
Shirai, Haruhiko [1 ]
Ogura, Hisakazu [1 ]
机构：
[1] Univ Fukui, Grad Sch Engn, Dept Nucl Power & Energy Safety Engn, Fukui 910, Japan
来源：
2013 NINTH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION (ICNC) | 2013年
关键词：
artificial fish swarm algorithm; symbiosis; host population; symbiont population; 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：
This paper presents a symbiosis-based artificial fish swarm algorithm (AFSA), which employs two artificial fish (AF) populations to collaboratively search the solution space of the problem to be solved. The symbiosis-based framework makes AF individuals adaptively adjust their Visual-limit and Step-limit. Due to the irrationality that AF individual swims toward its partners' geometric centre when gathering, a weighted centre and the method for calculating it was proposed. Beyond this, this paper also presents a newly designed behavioral strategy for AF. Experiments were conducted on several test functions. The results demonstrate good performance of the symbiosis-based AFSA when compared with several other swarm intelligence-based algorithms.
引用
收藏
页码：379 / 385
页数：7
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