Title :
A kind of Composite Shuffled Frog Leaping Algorithm
Author :
Zhang, Xiaodan ; Hu, Feng ; Tang, Jianeng ; Zou, Cairong ; Zhao, Li
Author_Institution :
Inst. of Inf. Sci. & Eng., Southeast Univ., Nanjing, China
Abstract :
In order to overcome the defects of Shuffled Frog Leaping Algorithm (SFLA) such as slow searching speed in the late evolution and easily trapping into local extremum, a Composite Shuffled Frog Leaping Algorithm (CSFLA) based on the basic idea of Artificial Fish-Swarm Algorithm (AFSA) is put forward in this paper in which the follow behavior of fish-swarm is used to accelerate the optimization speed and the swarm behavior to improve the capacity of out of local extremum. The test results indicate that CSFLA increases the convergence velocity outstandingly and enhances the global searching performance effectively.
Keywords :
artificial intelligence; convergence; heuristic programming; particle swarm optimisation; CSFLA; artificial fish-swarm algorithm; composite shuffled frog leaping algorithm; convergence velocity; local extremum capacity; post-heuristic computing technique; ptimization; Algorithm design and analysis; Convergence; Marine animals; Optimization; Particle swarm optimization; Robustness; Visualization; Artificial Fish-Swarm Algorithm (AFSA); Composite Shuffled Frog Leaping Algorithm (CSFLA); follow behavior; swarm behavior;
Conference_Titel :
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5958-2
DOI :
10.1109/ICNC.2010.5584419