Hybridizing artificial bee colony with biogeography-based optimization for constrained mechanical design problems
来源期刊：中南大学学报(英文版)2015年第6期
论文作者：CAI Shao-hong LONG Wen JIAO Jian-jun
文章页码：2250 - 2259
Key words：artificial bee colony; biogeography-based optimization; constrained optimization; mechanical design problem
Abstract: a novel hybrid algorithm named ABC-BBO, which integrates artificial bee colony (ABC) algorithm with biogeography-based optimization (BBO) algorithm, is proposed to solve constrained mechanical design problems. ABC-BBO combined the exploration of ABC algorithm with the exploitation of BBO algorithm effectively, and hence it can generate the promising candidate individuals. The proposed hybrid algorithm speeds up the convergence and improves the algorithm’s performance. Several benchmark test functions and mechanical design problems are applied to verifying the effects of these improvements and it is demonstrated that the performance of this proposed ABC-BBO is superior to or at least highly competitive with other population-based optimization approaches.
CAI Shao-hong(蔡绍洪)1, LONG Wen(龙文)1, JIAO Jian-jun(焦建军)1, 2
(1. Guizhou Key Laboratory of Economics System Simulation,
Guizhou University of Finance & Economics, Guiyang 550004, China;
2. School of Mathematics and Statistics, Guizhou University of Finance & Economics, Guiyang 550004, China)
Abstract:a novel hybrid algorithm named ABC-BBO, which integrates artificial bee colony (ABC) algorithm with biogeography-based optimization (BBO) algorithm, is proposed to solve constrained mechanical design problems. ABC-BBO combined the exploration of ABC algorithm with the exploitation of BBO algorithm effectively, and hence it can generate the promising candidate individuals. The proposed hybrid algorithm speeds up the convergence and improves the algorithm’s performance. Several benchmark test functions and mechanical design problems are applied to verifying the effects of these improvements and it is demonstrated that the performance of this proposed ABC-BBO is superior to or at least highly competitive with other population-based optimization approaches.
Key words:artificial bee colony; biogeography-based optimization; constrained optimization; mechanical design problem
