期刊名称：International Journal of Industrial Engineering Computations
印刷版ISSN：1923-2926
电子版ISSN：1923-2934
出版年度：2012
卷号：3
期号：4
页码：535-560
DOI：10.5267/j.ijiec.2012.03.007
语种：English
出版社：Growing Science Publishing Company
摘要：Nature inspired population based algorithms is a research field which simulates different natural phenomena to solve a wide range of problems. Researchers have proposed several algorithms considering different natural phenomena. Teaching-Learning-based optimization (TLBO) is one of the recently proposed population based algorithm which simulates the teaching-learning process of the class room. This algorithm does not require any algorithm-specific control parameters. In this paper, elitism concept is introduced in the TLBO algorithm and its effect on the performance of the algorithm is investigated. The effects of common controlling parameters such as the population size and the number of generations on the performance of the algorithm are also investigated. The proposed algorithm is tested on 35 constrained benchmark functions with different characteristics and the performance of the algorithm is compared with that of other well known optimization algorithms. The proposed algorithm can be applied to various optimization problems of the industrial environment.
关键词：Elitism; Population size; Teaching-learning-based optimization
