DocumentCode
1665608
Title
An improved FSOA based on stochastic search
Author
Wang Yong ; Lu Chuang ; Zhang Xin-zheng
Author_Institution
Coll. of Inf. Sci. & Eng., Guangxi Univ. for Nat., Nanning, China
fYear
2012
Firstpage
1601
Lastpage
1604
Abstract
In order to overcome the shortcoming of being trapped in local minima in basic FSOA(an optimization approach on using fishing strategy), an improving FSOA is presented based on stochastic search. The improving algorithm makes use of the stochastic searh approach and do not adopt the strategy of constricting search. It shows, from the experimental simulation results of some typical benchmark optimization problems and some typical restricted functions optimization problems, that the proposed optimization algorithm not only has great advantages of convergence property over basic FSOA, PSO and GA, but also can effectively avoid being trapped in local minima.
Keywords
convergence; optimisation; search problems; stochastic processes; GA; PSO; constricting search; convergence property; fishing strategy; improved FSOA; local minima; optimization algorithm; optimization approach; restricted function optimization problem; stochastic search; stochastic searh approach; Benchmark testing; Educational institutions; Genetic algorithms; Marine animals; Optimization; Particle swarm optimization; Stochastic processes; FSOA; IFSOA; fishing; optimization algorithm; stochastic search;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Automation Robotics & Vision (ICARCV), 2012 12th International Conference on
Conference_Location
Guangzhou
Print_ISBN
978-1-4673-1871-6
Electronic_ISBN
978-1-4673-1870-9
Type
conf
DOI
10.1109/ICARCV.2012.6485386
Filename
6485386
Link To Document