1. Simulated annealing teaching-learning-based optimization algorithm.
- Author
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CHEN De-bao, WEI Hua, ZOU Feng, WANG Jiang-tao, YANG Yi-jun, LI Zheng, and FANG Zhen-guo
- Subjects
SIMULATED annealing ,COMBINATORIAL optimization ,MACHINE learning ,EVOLUTIONARY computation ,MATHEMATICAL functions ,POPULATION dynamics - Abstract
This paper studied the problem that standard teaching-learning-based optimization algorithm (TLBO) easily converges to local optima when solving combinatorial optimization, and proposed a simulated annealing TLBO(SATLBO) algorithm. In the method, it used the simulated annealing algorithm. Randomly selected a bit of the bad individuals according to a calculated possibility of simulated annealing algorithm to the new population in the teacher phase and learner phase. It increased the ability of running away from local optima of TLBO by increasing the diversity of the population. It simulated the unmultimodal functions, multimodal functions and rotation functions, and compared the results with some other evolutionary computation algorithms. The results indicate that the improved algorithm has good performance in terms of convergence speed and accuracy. [ABSTRACT FROM AUTHOR]
- Published
- 2014
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