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Improved Elitist Teaching Learning Based Optimization to Enhance the Teacher Learning Performance

Author(s):

Trupti Ayachit , Alpine Institute of Technology; Amit Sariya, Alpine Institute of Technology

Keywords:

Data Mining, Optimization, MATLAB, Teaching–Learning-Based Optimization (TLBO), Elitist TLBO

Abstract

TLBO is a robust and effective search algorithm. The most salient advantage of this algorithm is that it does not require the tuning of any kind of controlling parameters. The principle idea behind TLBO is the simulation of teaching process in the traditional classroom. The performance of TLBO ends in two basic stages: (1) “teacher phase” or learning from the teacher, and (2) “learner phase” or trade off information between learners. MATLAB tool is used for the implementation of this model. In this work, another optimization construct approach with respect to TLBO is proposed. This methodology is utilized to enhance the outcomes. TLBO algorithm is adjusted and a versatile teaching factor is presented. Besides, more than one teacher is presented for the learners. The introduced adjustments improve the investigation and misuse limits of the fundamental TLBO algorithm. This work demonstrated different results that have been contrasted and past algorithms that came beforehand.

Other Details

Paper ID: IJSRDV6I120439
Published in: Volume : 6, Issue : 12
Publication Date: 01/03/2019
Page(s): 622-626

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