改进的基于教与学的优化算法

Junchang Zhai, Yuping Qin, Zhen Zhao, Minghai Yao
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引用次数: 11

摘要

为了提高TLBO算法对全局优化问题的优化性能,本文提出了一种带有新学习方案的改进TLBO (ITLBO)算法。在学习者阶段,非最优学生向随机选择的优秀学生学习,或者优秀学生根据两个相互学习者的适合度再向老师学习。为了评估所提出的ITLBO算法的性能,与TLBO算法进行了比较,对该问题进行了几种TLBO变体(A- TLBO、WTLBO、OTLBO、TLBO- gc)。最后,数值结果表明,该算法是求解全局优化问题的有效方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improved Teaching-Learning-Based Optimization Algorithm
To improve the optimization performance of the TLBO algorithm for global optimization problem, an improved TLBO (ITLBO) algorithm with new learning scheme is proposed in this paper. In the learner phase, a no-best student learns from a random selected excellent student or an excellent student learns from teacher again according the fitness of the two mutual learners. To evaluate the performance of the proposed ITLBO algorithm, comparison with TLBO algorithm, several TLBO variants (A- TLBO, WTLBO, OTLBO, TLBO-GC) for the problem is carried out. Finally, Numerical results show that the proposed algorithm is an effective method for global optimization problems.
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