Complex constrained design optimisation using an elitist teaching-learning-based optimisation algorithm Online publication date: Fri, 25-Jul-2014
by Ravipudi Venkata Rao; Gajanan Govindrao Waghmare
International Journal of Metaheuristics (IJMHEUR), Vol. 3, No. 1, 2014
Abstract: This paper presents the performance of an elitist teaching-learning-based optimisation algorithm on a class of constrained design optimisation problems. Teaching-learning-based optimisation (TLBO) is a recently proposed population-based algorithm which simulates the teaching-learning process of the class room. This algorithm requires only the common control parameters and does not require any algorithm-specific control parameters. The effect of elitism on the performance of the TLBO algorithm is investigated in this paper while solving the constrained benchmark problems. The effects of common control parameters such as the population size and the number of generations on the performance of the algorithm are also investigated. Twenty-one benchmark problems taken from the literature related to constrained design optimisation are used to test the elitist TLBO performance. Experimental results show that the elitist TLBO is superior or competitive to other optimisation algorithms for the problems considered.
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