Abstract
Teaching Learning Based Optimization (TLBO) is being used as a new, reliable, accurate and robust optimization technique scheme for global optimization over continuous spaces. This paper presents an effect of variation of a teaching factor TF in traditional TLBO algorithm and then proposed a value for teaching factor TF. The traditional TLBO algorithm with new teaching factor TF value has been tested on several benchmark functions and shown to be statistically significantly better than other teaching factor values for performance measures in terms of faster convergence behavior.
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Murty, M.R., Murthy, J.V.R., Reddy, P.V.G.D.P., Naik, A., Satapathy, S.C. (2014). Performance of Teaching Learning Based Optimization Algorithm with Various Teaching Factor Values for Solving Optimization Problems. In: Satapathy, S., Udgata, S., Biswal, B. (eds) Proceedings of the International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA) 2013. Advances in Intelligent Systems and Computing, vol 247. Springer, Cham. https://doi.org/10.1007/978-3-319-02931-3_25
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DOI: https://doi.org/10.1007/978-3-319-02931-3_25
Publisher Name: Springer, Cham
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