Fuzzy adaptive teaching–learning-based optimization for global numerical optimization

2016 ◽  
Vol 29 (2) ◽  
pp. 309-327 ◽  
Author(s):  
Min-Yuan Cheng ◽  
Doddy Prayogo
Keyword(s):  
Numerical Optimization ◽  
Global Numerical Optimization ◽  
Adaptive Teaching ◽  
Teaching Learning Based Optimization ◽  
Teaching Learning ◽  
Fuzzy Adaptive

scholarly journals Chaotic Teaching-Learning-Based Optimization with Lévy Flight for Global Numerical Optimization

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Xiangzhu He ◽  
Jida Huang ◽  
Yunqing Rao ◽  
Liang Gao
Keyword(s):  
Numerical Optimization ◽  
Large Scale ◽  
Heuristic Algorithms ◽  
Lévy Flight ◽  
Global Numerical Optimization ◽  
Levy Flight ◽  
Local Optima ◽  
Teaching Learning Based Optimization ◽  
Teaching Learning ◽  
Different Characteristics

Recently, teaching-learning-based optimization (TLBO), as one of the emerging nature-inspired heuristic algorithms, has attracted increasing attention. In order to enhance its convergence rate and prevent it from getting stuck in local optima, a novel metaheuristic has been developed in this paper, where particular characteristics of the chaos mechanism and Lévy flight are introduced to the basic framework of TLBO. The new algorithm is tested on several large-scale nonlinear benchmark functions with different characteristics and compared with other methods. Experimental results show that the proposed algorithm outperforms other algorithms and achieves a satisfactory improvement over TLBO.

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