Advance Teaching–Learning Based Optimization for Global Function Optimization

  • Anand Verma
  • Shikha Agrawal
  • Jitendra Agrawal
  • Sanjeev Sharma
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 43)

Abstract

Teaching–Learning based optimization (TLBO) is an evolutionary powerful algorithm in optimal solutions search space that is inspired from teaching learning phenomenon of a classroom. It is a novel population based algorithm with faster convergence speed and without any algorithm specific parameters. The present work proposes an improved version of TLBO called the Advance Teaching–Learning Based Optimization (ATLBO). In this algorithm introduced a new weight parameter for more accuracy and faster convergence rate. The effectiveness of the method is compare against original TLBO on many benchmark problems with different characteristics and shows the improvement in performance of ATLBO over traditional TLBO.

Keywords

Global function optimization Teaching-learning based optimization (TLBO) Population based algorithms Convergence speed 

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Copyright information

© Springer India 2016

Authors and Affiliations

  • Anand Verma
    • 1
  • Shikha Agrawal
    • 2
  • Jitendra Agrawal
    • 1
  • Sanjeev Sharma
    • 1
  1. 1.School of Information TechnologyRajiv Gandhi Proudyogiki VishwavidyalayaBhopalIndia
  2. 2.University Institute of TechnologyRajiv Gandhi Proudyogiki VishwavidyalayaBhopalIndia

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