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
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;
Conference_Titel :
Advanced Computational Intelligence (IWACI), 2011 Fourth International Workshop on
Conference_Location :
Wuhan
Print_ISBN :
978-1-61284-374-2
DOI :
10.1109/IWACI.2011.6160087