Teaching-learning-based optimization (TLBO) algorithm is a novel heuristic method which simulates the teaching-learning\nphenomenon of a classroom. However, in the later period of evolution of the TLBO algorithm, the lower exploitation ability and\nthe smaller scope of solutions led to the poor results. To address this issue, this paper proposes a novel version of TLBO that is\naugmented with error correction strategy and Cauchy distribution (ECTLBO) in which Cauchy distribution is utilized to expand\nthe searching space and error correction to avoid detours to achieve more accurate solutions. The experimental results verify that\nthe ECTLBO algorithm has overall better performance than various versions of TLBO and is very competitive with respect to\nother nine original intelligence optimization algorithms. Finally, the ECTLBO algorithm is also applied to path planning of\nunmanned aerial vehicle (UAV), and the promising results show the applicability of the ECTLBO algorithm for problem-solving.
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