Teaching-Learning-Based Optimization Algorithm for Dealing with Real-Parameter Optimization Problems
Year: 2013
Type: article
Abstract: A latest optimization algorithm, named Teaching-Learning-Based Optimization (simply TLBO) was proposed by R. V. Rao et al, at 2011. Afterwards, some improvements and practical applications have been conducted toward TLBO algorithm. However, as far as our knowledge, there are no such works which categorize the current works concerning TLBO from the algebraic and analytic points of view. Hence, in this paper we firstly introduce the concepts and algorithms of TLBO, then survey the running mechanism of TLBO for dealing with the real-parameter optimization problems, and finally group its real-world applications with a categorizing framework based on the clustering, multi-objective optimization, parameter optimization, and structure optimization. The main advantage of this work is to help the users employ TLBO without knowing details of this algorithm. Meanwhile, we also give an experimental comparison for demonstrating the effectiveness of TLBO on 5 benchmark evaluation functions and conclude this work by identifying trends and challenges of TLBO research and development.
Source: Applied Mechanics and Materials
Authors: Kai Lin Wang, Hui Bin Wang, Li Xia Yu, Xue Yu Ma, Yun Sheng Xue
Institution: Xingtai University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W1983204940