Suresh Chandra Satapathy, Anima Naik, K. Parvathi
Anil Neerukonda Institute of Technology and Sciences, Vishakapatnam, India.
Centurion University of Technology and Management, Paralakhemundi, India.
Majhighariani Institute of Technology & Science, Rayagada, India.
DOI: 10.4236/am.2013.43064   PDF    HTML   XML   6,683 Downloads   11,937 Views   Citations

Abstract

Teaching-Learning-Based Optimization (TLBO) is recently being used as a new, reliable, accurate and robust optimization technique scheme for global optimization over continuous spaces [1]. This paper presents an, improved version of TLBO algorithm, called the Weighted Teaching-Learning-Based Optimization (WTLBO). This algorithm uses a parameter in TLBO algorithm to increase convergence rate. Performance comparisons of the proposed method are provided against the original TLBO and some other very popular and powerful evolutionary algorithms. The weighted TLBO (WTLBO) algorithm on several benchmark optimization problems shows a marked improvement in performance over the traditional TLBO and other algorithms as well.

Keywords

Function Optimization; TLBO; Evolutionary Computation

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Conflicts of Interest

The authors declare no conflicts of interest.

References

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