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融合模拟退火的改进教与学优化算法 被引量：5

Modified Teaching-Learning-Based Optimization Algorithm by Using Simulated Annealing
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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. 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 algo- rithm is better than basic TLBO algorithm, ETLBO algorithm and DMTLBO algorithm in terms of convergence speed and search precision.
作者 岳振芳 高岳林
机构地区 宁夏大学数学计算机学院 北方民族大学信息与系统科学研究所
出处 《河南师范大学学报（自然科学版）》 CAS 北大核心 2016年第1期149-154,共6页 Journal of Henan Normal University(Natural Science Edition)
基金 国家自然科学基金(61561001) 北方民族大学重点科研项目(2015KJ10)
关键词 教与学优化算法 模拟退火算法 局部最优 teaching-learning-based optimization algorithm simulated annealing algorithm local optima
分类号 TP18 [自动化与计算机技术—控制理论与控制工程]
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参考文献12

  • 1Rao R V, Savsani V J, Vakharia D P. Teaching-learningbased optimization: a novel method for constrained mechanical design optimiza- tion problems[J]. Computer Aided Design, 2011,43(3) : 303-315.
  • 2Rao R V, Savsani V J, Vakharia D P. Teaching-learning-based optimization: an optimization method for continuous non-linear large scaleproblemsI-J]. Information Sciences,2012,183(1) :1-15.
  • 3Rao R V, Savsani V J, Balic J. Teaching-learning-based optimization algorithm for unconstrained and constrained real parameter optimi- zation problems[J]. Engineering Optimization,2012,44(2) : 1447-1462.
  • 4Rao R V, Patel V. Multi-objective optimization of heat exchangers using a modified teaching-learning-based optimization algorithm[J]. Applied Mathematical Modeling, 2013,37(3) : 1147-1162.
  • 5Rao R V, Patel V. Multi-objective optimization of two stage thermoelectric coolers using amodified Teaching-learning-based optimization algorithm[J]. Engineering Applications of Artificial Intelligence, 2013,26(1):430-445.
  • 6Crepinsek M, Liu S H, Mernik L, A note on teaching-learning-based optimization aigorithm[J]. Information Sciences, 2012,212 (1)~ 79- 93.
  • 7Rao R V, Patel V. An elitist teaching-learning-based optimization algorithm for solving complex constrained optimization problems[J]. International Journal, 2012,3 (4) : 535-560.
  • 8李会荣,乔希民,赵鹏军.融合差分变异的教一学优化算法[J].计算机工程与应用,2014,50(22):1-6.
  • 9Rao R V, Patel V. An improved teaching-learning-based optimization algorithm for solving nuconstrained optimization problems[J]. Sci- entai Iranica,2013,20(3) :710-720.
  • 10拓守恒.一种优化神经网络的教与学优化算法[J].智能系统学报,2013,8(4):327-332. 被引量：14

二级参考文献13

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共引文献13

同被引文献31

引证文献5

二级引证文献10

河南师范大学学报（自然科学版）
2016年 第1期

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