Cooperative Bacterial Foraging Algorithm for Global Optimization
Bacterial Foraging Optimization (BFO) is a novel optimization algorithm based on the social foraging behavior of E. coli bacteria. However, the original BFO algorithm possesses a poor convergence behavior compared to the other successful nature-inspired algorithms. In order to accelerate the convergence speed of the bacterial colony near global optima, two cooperative approaches have been applied to BFO that resulted in a significant improvement in the performance of the original algorithm in terms of convergence speed, accuracy and robustness. The performance of the proposed cooperative variants are compared to the original BFO, the standard PSO, and a real-coded GA on a set of 4 widely-used benchmark functions, demonstrating their superiority.
Bacterial Foraging Optimization Cooperative BFO PSO GA
Hanning Chen Yunlong Zhu Kunyuan Hu
Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, 110016, China
国际会议
2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)
广西桂林
英文
3896-3901
2009-06-17（万方平台首次上网日期，不代表论文的发表时间）