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Improved version of teaching learning-based optimization algorithm using random local search: TLBO-RLS

Bourahla Kheireddine (Department of Electrical, Universite de Jijel, Jijel, Algeria)
Belli Zoubida (Department of Electrical, Universite de Jijel, Jijel, Algeria)
Hacib Tarik (Department of Electrical, Universite de Jijel, Jijel, Algeria)

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering

ISSN: 0332-1649

Article publication date: 3 June 2019

Issue publication date: 3 June 2019

104

Abstract

Purpose

This paper aims to deal with the development of a newly improved version of teaching learning based optimization (TLBO) algorithm.

Design/methodology/approach

Random local search part was added to the classic optimization process with TLBO. The new version is called TLBO algorithm with random local search (TLBO-RLS).

Findings

At first step and to validate the effectiveness of the new proposed version of the TLBO algorithm, it was applied to a set of two standard benchmark problems. After, it was used jointly with two-dimensional non-linear finite element method to solve the TEAM workshop problem 25, where the results were compared with those resulting from classical TLBO, bat algorithm, hybrid TLBO, Nelder–Mead simplex method and other referenced work.

Originality value

New TLBO-RLS proposed algorithm contains a part of random local search, which allows good exploitation of the solution space. Therefore, TLBO-RLS provides better solution quality than classic TLBO.

Keywords

Citation

Kheireddine, B., Zoubida, B. and Tarik, H. (2019), "Improved version of teaching learning-based optimization algorithm using random local search: TLBO-RLS", COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, Vol. 38 No. 3, pp. 1048-1060. https://doi.org/10.1108/COMPEL-09-2018-0373

Publisher

:

Emerald Publishing Limited

Copyright © 2019, Emerald Publishing Limited

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