摘要
针对教-学优化算法(TLBO)求解无约束数值优化问题容易陷入局部最优的不足,提出了一种带有交叉操作的教-学优化算法(C-TLBO).将差分进化算法的交叉操作引入到TLBO算法中,有效地融合了教学阶段和学习阶段,增强了算法的局部搜索,平衡了算法的开采和探索.数值结果表明该算法在优化精度、收敛速度、鲁棒性方面,优于TLBO算法、I-TLBO算法以及其他智能优化算法,具有良好的发展前景.
Since the teaching-learning based optimization （TLBO） algorithm was easily trapped into local optima in solving unconstrained numerical optimization problems, a teaching-learning based optimization algorithm with crossover operation was proposed. The crossover operation of differential evolution was incorporated into TLBO, this operation was effectively integrating teaching and learning stage and it was beneficial to enhance local search and balance exploitation and exploration. The numerical results show that the proposed algorithm is better than TLBO, I-TLBO and other intelligent methods in terms of optimization precision, convergence speed and robustness, and the algorithm has good perspectives.
出处
《东北大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2014年第3期323-327,共5页
Journal of Northeastern University(Natural Science)
基金
国家自然科学基金资助项目(61273155)
关键词
教-学优化算法
局部最优
交叉操作
开采
探索
teaching-learning based optimization algorithm
local optima
crossover operation
exploitation
exploration
