DocumentCode :
3418537
Title :
Improved opposition-based biogeography optimization
Author :
Yang, Xin ; Cao, Jiangtao ; Li, Kairu ; Li, Ping
Author_Institution :
Sch. of Inf. & Control Eng., Liaoning Shihua Univ., Fushun, China
fYear :
2011
fDate :
19-21 Oct. 2011
Firstpage :
642
Lastpage :
647
Abstract :
Biogeography-Based Optimization (BBO) is a recently developed global optimization algorithm and has shown its ability to solve complex optimization problem. In order to speed the optimization process and get better results, an improved opposition-based biogeography optimization (IOBBO) method is proposed. By dividing the range of values into several areas, the proposed method produce more evenly distributed initial population. Considering some of the optimal values are not in the center of the problem domain, in this paper, the current optimal solution is introduced. In the process of taking the opposite populations, the current optimal solution is instead with the range of the upper and lower limits. Experiments results clearly showed that the IOBBO outperforms the opposition-based biog eography optimization(OBBO) and improvement of Opposition-based Differential Evolution(IODE) on five benchmark test functions.
Keywords :
optimisation; complex optimization problem; evenly distributed initial population; global optimization algorithm; improved opposition-based biogeography optimization; opposition-based differential evolution; optimal solution; optimization process; Algorithm design and analysis; Benchmark testing; Biogeography; Educational institutions; Indexes; Mathematical model; Optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Computational Intelligence (IWACI), 2011 Fourth International Workshop on
Conference_Location :
Wuhan
Print_ISBN :
978-1-61284-374-2
Type :
conf
DOI :
10.1109/IWACI.2011.6160087
Filename :
6160087
Link To Document :
بازگشت