摘要
针对标准细菌觅食优化算法（BFOA）求解精度不高、稳定性较差、容易陷入局部极值的问题,提出了一种基于模拟退火策略的细菌觅食优化算法（SA-BFO）。该算法在趋向操作完成后,采用模拟退火策略对全局最优个体进行优化,提高算法的优化精度和稳定性,利用模拟退火算法的概率突跳性来避免陷入局部极值。仿真实验结果表明,改进算法比标准细菌觅食优化算法具有较高的优化性能。
Aiming at the problems of standard bacteria foraging optimization algorithm（BFOA）’s lowly search accuracy,poorly sta bility,easily to trap into local extremum,proposes a bacteria foraging optimization algorithm based on simulated annealing atrategy（SA-BFO）.the algorithm adopts the strategy of simulated annealing to optimize the global optimal individual after chemotaxis,im prove the optimization precision and stability of the algorithm,uses the probability kick of simulated annealing algorithm to avoid falling into local extremum.The simulation experimental results show that the improved algorithm has better optimized perfor mance than the standard bacteria foraging optimization algorithm.
作者
王红
王联国
WANG Hong,WANG Lian-guo（College of Information Science and Technology,Gansu Agricultural University,Lanzhou 730070,China）
出处
《电脑知识与技术》
2013年第4期2442-2445,2458,共5页
Computer Knowledge and Technology
基金
甘肃省教育信息化发展战略研究项目（2011-02）
关键词
细菌觅食优化算法
模拟退火
概率突跳性
精度
稳定性
bacteria foraging optimization algorithm
simulated annealing
probability kick
precision
stability
