Chaotic Fruit Fly Optimization Algorithm

被引：0

作者：

Lei, Xiujuan ^{[1
,2
]}

Du, Mingyu

Xu, Jin ^{[1
]}

Tan, Ying ^{[1
]}

机构：

[1] Peking Univ, Sch Elect Engn & Comp Sci, Beijing 100871, Peoples R China

[2] Shaanxi Normal Univ, Sch Comp Sci, Xian 710062, Peoples R China

来源：

ADVANCES IN SWARM INTELLIGENCE, PT1 | 2014年 / 8794卷

基金：

中国国家自然科学基金;

关键词：

Fruit fly optimization; logistic chaos; function optimization; NEURAL-NETWORK; SYSTEM; MODEL;

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：

Fruit fly optimization algorithm (FOA) was a novel swarm intelligent algorithm inspired by the food finding behavior of fruit flies. Due to the deficiency of trapping into the local optimum of FOA, a new fruit fly optimization integrated with chaos operation (named CFOA) was proposed in this paper, in which logistic chaos mapping was introduced into the movement of the fruit flies, the optimum was generated by both the best fruit fly and the best fruit fly in chaos. Experiments on single-mode and multi-mode functions show CFOA not only outperforms the basic FOA and other swarm intelligence optimization algorithms in both precision and efficiency, but also has the superb searching ability.

引用

页码：74 / 85

页数：12

共 35 条

[1]

[Anonymous], 2011 C DIG TECHN INN

[2] Honey-bees mating optimization (HBMO) algorithm:: A new heuristic approach for water resources optimization [J].