International Journal of Computational Intelligence Systems

Volume 9, Issue 3, June 2016, Pages 506 - 524

An autonomous teaching-learning based optimization algorithm for single objective global optimization

Authors
Fangzhen Ge*, Liurong Hong, Li Shi
School of Computer Science and Technology, Huaibei Normal University, Huaibei 235000, China
*Corresponding author. E-mail: [email protected].
Corresponding Author
Fangzhen Ge
Received 2 November 2015, Accepted 22 February 2016, Available Online 1 June 2016.
DOI
10.1080/18756891.2016.1175815How to use a DOI?
Keywords
Teaching-Learning Based Optimization; Global Optimization; Autonomy; Learning Desires
Abstract

Teaching-learning based optimization is a newly developed intelligent optimization algorithm. It imitates the process of teaching and learning simply and has better global searching capability. However, some studies have shown that TLBO is good at exploration but poor at exploitation and often falls into local optimum for certain complex problems. To address these issues, a novel autonomous teaching-learning based optimization algorithm is proposed to solve the global optimization problems on the continuous space. Our proposed algorithm is remodeled according to the three phases of the teaching and learning process, learning from a teacher, mutual learning and self-learning among students instead of two phases of the original one. Moreover, the motivation and autonomy of students are considered in our proposed algorithm, and the expressions of autonomy are formulated. The performance of our proposed algorithm is compared with that of the related algorithms through our experimental results. The results indicate the proposed algorithm performs better in terms of the convergence and optimization capability.

Copyright
© 2016. the authors. Co-published by Atlantis Press and Taylor & Francis
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
9 - 3
Pages
506 - 524
Publication Date
2016/06/01
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.1080/18756891.2016.1175815How to use a DOI?
Copyright
© 2016. the authors. Co-published by Atlantis Press and Taylor & Francis
Open Access
This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Fangzhen Ge
AU  - Liurong Hong
AU  - Li Shi
PY  - 2016
DA  - 2016/06/01
TI  - An autonomous teaching-learning based optimization algorithm for single objective global optimization
JO  - International Journal of Computational Intelligence Systems
SP  - 506
EP  - 524
VL  - 9
IS  - 3
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2016.1175815
DO  - 10.1080/18756891.2016.1175815
ID  - Ge2016
ER  -