计算机应用与软件Issue(2)：246-249,298,5.DOI:10.3969/j.issn.1000-386x.2016.02.057
多学习教与学优化算法
TEACHING-LEARNING-BASED OPTIMISATION ALGORITHM WITH MULTI-LEARNING STRATEGY
摘要
Abstract
We proposed a teaching-learning-based optimisation algorithm (TLBO)with multi-learning mechanism (MTLBO),which is based on the opposition-based learning,aimed at the drawbacks of basic TLBO in poor local development ability and solutions being prone to falling into local optima.It broadens the search space through opposition-based learning technology to increase the diversity of solutions and further improve the global search ability of the algorithm.The introduction of multi-learning mechanism makes the local search more effective and speeds up the convergence rate.Meanwhile we presented a small probability mutation strategy to increase the likelihood of solutions jumping out of local optima.Verification experiments were carried out on benchmark test functions,results indicated that compared with basic TLBO,ITLBO and other optimised algorithms,the proposed MTLBO algorithm achieved better optimisation effect on both low and high dimensional functions.关键词
教与学优化算法/反向学习技术/多学习机制/变异策略Key words
Teaching-learning-based optimisation algorithm/Opposition-based learning technology/Multi-learning mechanism/Mutation strategy分类
信息技术与安全科学引用本文复制引用
李志南,南新元,李娜,史德生..多学习教与学优化算法[J].计算机应用与软件,2016,(2):246-249,298,5.基金项目
新疆“十二五”制造业信息化科技示范工程项目（201130110）。 （）
