Toward Teaching-Learning-Based Optimization Algorithm for Dealing with Real-Parameter Optimization Problems
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.
Teaching-Learning-Based Optimization clustering multi-objective optimization
Kai-Lin Wang Hui-Bin Wang Li-Xia Yu Xue-Yu Ma Yun-Sheng Xue
The Academic Affairs Office,Xingtai University,Xingtai 054001,Hebei,China The Human Resources Office,Xingtai University,Xingtai 054001,Hebei,China The Department of Education Science,Xingtai University,Xingtai 054001,Hebei,China The Foreign Affairs Office,Xingtai University,Xingtai 054001,Hebei,China
国际会议
杭州
英文
606-609
2013-03-22（万方平台首次上网日期，不代表论文的发表时间）