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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Rao, R.V., Savsani, V.J., Vakharia, D.P.: Teaching–learning-based optimization: an optimization method for continuous non-linear large scale problems. Inf. Sci. 183, 1–15 (2012)
Rao, R.V., Patel, V.: An elitist teaching-learning-based optimization algorithm for solving complex constrained optimization problems. Int. J. Ind. Eng. Comput. 3, 535–560 (2012)
Rao, R.V., Patel, V.: An improved teaching-learning-based optimization algorithm for solving unconstrained optimization problems. Scientia Iranica D 20(3), 710–720 (2013)
Rao, R.V., Patel, V.: A multi-objective improved teaching–learning based optimization algorithm for unconstrained and constrained optimization problems. Int. J. Ind. Eng. Comput. 5, 1–22 (2014)
Wang, K., et al.: Toward teaching-learning-based optimization algorithm for dealing with real-parameter optimization problems. In: Proceeding of the 2nd International Conference on Computer Science and Electronics Engineering (2013)
Rai, S., Mishra, S.K., Dubey, M.: Teacher learning based optimization of assignment model. Int. J. Mech. Prod. Eng. Res. Dev. 3(5), 61–72 (2013)
Satapathy, S.C., Nail, A., Parvathi, K.,: A teaching learning based optimization based on orthogonal design for solving global optimization problems. SpringerPlus 2,130 (2013)
Satapathy, S.C., Nail, A.: Improved teaching learning based optimization for global function optimization. Decis. Sci. Lett. 2, 23–24 (2012)
Satapathy, S.C., Nail, A., Parvathi, k: Weighted teaching-learning-based optimization for global function optimization. Sci. Res. Appl. Math. 4, 429–439 (2013)
Sahu, A., Sushantak, P.K., Sabyasachi, P.: An empirical study on classification using modified teaching learning based optimization. IJCSN Int. J. Comput. Sci. Netw. 2(2) (2013)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer India
About this paper
Cite this paper
Verma, A., Agrawal, S., Agrawal, J., Sharma, S. (2016). Advance Teaching–Learning Based Optimization for Global Function Optimization. In: Nagar, A., Mohapatra, D., Chaki, N. (eds) Proceedings of 3rd International Conference on Advanced Computing, Networking and Informatics. Smart Innovation, Systems and Technologies, vol 43. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2538-6_59
Download citation
DOI: https://doi.org/10.1007/978-81-322-2538-6_59
Published:
Publisher Name: Springer, New Delhi
Print ISBN: 978-81-322-2537-9
Online ISBN: 978-81-322-2538-6
eBook Packages: EngineeringEngineering (R0)