摘要
教与学优化算法(TLBO)是一种基于班级教学过程和学习过程的新型智能优化算法。针对TLBO算法全局搜索能力较差,容易陷入局部最优的问题,提出了一种改进的教与学优化算法(ITLBO)。通过加入反馈阶段,使得成绩较差的学生与教师及时进行反馈交流,提高了算法的寻优精度;同时,为了克服早熟收敛现象,引入准确性因子,维持了种群多样性。数值试验表明ITLBO算法比基本TLBO算法在收敛速度和寻优精度上更具有优势。
Teaching-Leaching-Based Optimization（TLBO） algorithm is a new intelligent optimization algorithm based on the teaching-learning process of the class. An improved teaching-learning-based optimization（ITLBO） is proposed to solve the problems of the poor global search ability and easy trapping in local optimum of the TLBO. The feedback phase is introduced to increase the learning way and promotes the mutual communication between poor students and the teacher, which the fine local search improves the precision. Moreover, the accuracy factor is proposed to strengthen the diversity of population and avoid the premature convergence phenomenon. The results on the benchmark functions showed that the ITLBO algorithm outperforms the basic TLBO algorithm in convergence speed and search precision.
出处
《商洛学院学报》
2016年第2期1-5,24,共6页
Journal of Shangluo University
基金
陕西省教育厅专项科研计划项目(15JK1221)
关键词
教与学优化
反馈阶段
准确性因子
函数优化
Teaching-Learning-Based Optimization
feedback phase
accuracy factor
function optimization
