Comments on "A note on teaching-learning-based optimization algorithm"

Authors:
Gajanan Waghmare
Affiliations:
Department of Mechanical Engineering, K.K. Wagh Institute of Engineering Education and Research, Amrutdham, Panchavati, Nasik 422 003, India
Venue:
Information Sciences: an International Journal
Year:
2013

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Abstract

A note published by Crepinsek et al. [3] (A note on teaching-learning-based optimization algorithm, Information Sciences 212 (2012) 79-93) reported three ''important mistakes'' regarding teaching-learning-based optimization (TLBO) algorithm. Furthermore, the authors had presented some experimental results for constrained and unconstrained benchmark functions and tried to invalidate the performance supremacy of the TLBO algorithm. However, the authors had not reviewed the latest research literature on TLBO algorithm and their observations about TLBO algorithm were based only on two papers that were published initially. The views and the experimental results presented by Crepinsek et al. [3] are questionable and this paper re-examines the experimental results and corrects the understanding about the TLBO algorithm in an objective manner. The latest literature on TLBO algorithm is also presented and the algorithm-specific parameter-less concept of TLBO is explained. The results of the present work demonstrate that the TLBO algorithm performs well on the problems where the fitness-distance correlations are low by proper tuning of the common control parameters of the algorithm.