细菌觅食优化算法是近年来发展起来的,基于大肠杆菌觅食行为模型的一种新型智能算法。它具有对初值和参数选择不敏感、鲁棒性强、简单易于实现,以及并行处理和全局搜索等优点。但其在应用过程中存在精度不够高、收敛速度不够快的缺点。文中首先对细菌觅食优化算法的基本原理及操作流程进行介绍,并概述了国内外学者在这一领域的研究现状,接着分析了算法三大主要操作存在的问题,然后探讨了算法的改进和应用,最后分析了算法未来的研究方向。
Bacterial Foraging Optimization Algorithm ( BFOA) is one of the new intelligent optimization methods that are based on the simulation of the foraging of Escherichia Coli. The advantage of BFO is the insensitivity of parameter choosing,robustness,parallel computing and easily global searching and so on. But during the superficial application the weakness of relatively low accuracy and rate of convergence is discovered. First introduce the basic principle and operation process for the BFOA,and overview the current researches of many domestic and international scholars about BFOA. Then analyze the three major problems existing in the operation algorithm. And then the improvement and application of BFOA are discussed. Finally,the future research direction of the algorithm is analyzed.