4.2 Article

A Novel Teaching-Learning-Based Optimization with Error Correction and Cauchy Distribution for Path Planning of Unmanned Air Vehicle

Journal

COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE
Volume 2018, Issue -, Pages -

Publisher

HINDAWI LTD
DOI: 10.1155/2018/5671709

Keywords

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Funding

  1. National Natural Science Foundation of China [51575442, 61402361]
  2. Research Fund for the Doctoral Program of Higher Education of China [17129033029]
  3. Natural Science Foundation of Hebei Province [F2017402069]

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

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