An activity improved bacterial foraging optimization and its performance analysis

作者：Zhao Fuqing^*; Jiang Xin; Wang Junbiao

来源：Journal of Computational Information Systems, 2013, 9(18): 7397-7405.

DOI：10.12733/jcisP0202

• Bacteria foraging optimizations
• Bacterial foraging optimization
• Chemotaxis
• Difference evolution
• Differential Evolution
• High-dimensional problems
• Performance analysis
• Stationary problem

This paper proposes an activity improved bacterial optimization (AIBFO) aims to solve the stationary problem that cause by the failure tumbling in chemotaxis of the original Bacterial Foraging Optimization. The novel algorithm introduces a differential evolution operator into the chemotactic operation to optimize the stationary bacterium after their failing tumble in order to improve the effectiveness of chemotaxis. The evolution method and convergence of the algorithm have been proved theoretically in the paper. Typical example experiments show that the novel algorithm has great ability of avoiding the local optimum and performs a faster convergent speed and search accuracy in solving high dimensional problems.

• 出版日期2013
• 单位西北工业大学