An Improved Fireworks Algorithm Based on Grouping Strategy of the Shuffled Frog Leaping Algorithm to Solve Function Optimization Problems

被引：5
|
作者：
Sun, Yu-Feng [1 ]
Wang, Jie-Sheng [1 ,2 ]
Song, Jiang-Di [1 ]
机构：
[1] Univ Sci & Technol Liaoning, Sch Elect & Informat Engn, Anshan 114044, Peoples R China
[2] Univ Sci & Technol Liaoning, Natl Financial Secur & Syst Equipment Engn Res Ct, Anshan 114044, Peoples R China
来源：
ALGORITHMS | 2016年 / 9卷 / 02期
关键词：
fireworks algorithm; shuffled frog leaping algorithm; grouping strategy; function optimization;
D O I：
10.3390/a9020023
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The fireworks algorithm (FA) is a new parallel diffuse optimization algorithm to simulate the fireworks explosion phenomenon, which realizes the balance between global exploration and local searching by means of adjusting the explosion mode of fireworks bombs. By introducing the grouping strategy of the shuffled frog leaping algorithm (SFLA), an improved FA-SFLA hybrid algorithm is put forward, which can effectively make the FA jump out of the local optimum and accelerate the global search ability. The simulation results show that the hybrid algorithm greatly improves the accuracy and convergence velocity for solving the function optimization problems.
引用
收藏
页数：11
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