首页 | 本学科首页   官方微博 | 高级检索  
     检索      

融合模拟退火的改进教与学优化算法
作者单位:;1.宁夏大学数学计算机学院;2.北方民族大学信息与系统科学研究所
摘    要:针对教与学优化算法(TLBO)在解决复杂优化问题时易陷入局部最优的缺点,提出了一种融合模拟退火的改进教与学优化算法(SAMTLBO).该算法首先对学员阶段做了改进,在保持TLBO算法简单易实现的基础上,利用模拟退火方法增强了TLBO算法摆脱局部最优的能力,最后用4种算法对8个无约束优化函数仿真.数值实验表明,该算法无论是在收敛速度还是在寻优精度上均优于基本TLBO算法、ETLBO算法和DMTLBO算法.

关 键 词:教与学优化算法  模拟退火算法  局部最优

Modified Teaching-Learning-Based Optimization Algorithm by Using Simulated Annealing
Institution:,School of Mathematics and Computer Science,Ningxia University,Research Institute of Information and System Science,Beifang University of Nationalities
Abstract:As for the disadvantage in local optima of Teaching-Learning-Based Optimization algorithm(TLBO)in solving complex optimization problem,a modified Teaching-Learning-Based Optimization by using simulated annealing(SAMTLBO)is proposed.The algorithm firstly makes an improvement in students stage.On the basic of keep TLBO easily implement and we utilize simulated annealing method to enhance TLBO algorithm to get rid of the ability of its local optimum.Finally we apply four kinds of algorithms to simulate nu-constrained optimization functions.Numerical experiments show that SAMTLBO algorithm is better than basic TLBO algorithm,ETLBO algorithm and DMTLBO algorithm in terms of convergence speed and search precision.
Keywords:teaching-learning-based optimization algorithm  simulated annealing algorithm  local optima
本文献已被 CNKI 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号