分析了细菌觅食优化(BFO)算法的原理以及当前的研究状况,主要根据心理学家爱德华.桑代克(E L Thordike)的经典效果律和经济学家巴菜多的巴莱多定律等对标准BFO算法存在的不足进行改进;将改进后的BFO算法在函数优化问题上进行仿真实验,实验结果表明改进后的BFO算法比标准BFO算法具有更快的收敛速度和更强的搜索性能。
The principle of the Bacterial Foraging Optimization (BFO) algorithm as well as the current research status is ana- lyzed firstly, then the standard BFO algorithm is improved to overcome its insufficiency mainly based on the classic effect law of psychologist Edward Thorndike grams (E L Thordike) and the Pareto' s law of economist Pareto. The experimental results on Benchmark function optimization problems show that the improved BFO algorithm has the higher searching performance and convergence rate than the standard BFO algorithm.