Advances in teaching–learning-based optimization algorithm: A comprehensive survey(ICIC2022)

•Teaching-learning-based optimization (TLBO) is one of population-based heuristic stochastic swarm intelligent algorithm.•In this paper, a comprehensive survey on the recent advances in TLBO is presented.•Literature survey reveals some interesting challenges and future research directions. Teaching-...

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Bibliographic Details
Published in:	Neurocomputing (Amsterdam) Vol. 561; p. 126898
Main Authors:	Zhou, Guo, Zhou, Yongquan, Deng, Wu, Yin, Shihong, Zhang, Yunhui
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 07.12.2023
Subjects:	Metaheuristic Optimization Optimization problem Population-based Teaching–learning-based optimization algorithm Teaching–learning-based optimization algorithm Metaheuristic Population-based Optimization Optimization problem
ISSN:	0925-2312
Online Access:	Get full text
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Summary:	•Teaching-learning-based optimization (TLBO) is one of population-based heuristic stochastic swarm intelligent algorithm.•In this paper, a comprehensive survey on the recent advances in TLBO is presented.•Literature survey reveals some interesting challenges and future research directions. Teaching-learning-based optimization (TLBO) algorithm which imitates the teaching–learning process in a classroom, is one of population-based heuristic stochastic swarm intelligent algorithms. TLBO executes through similar iterative evolution processes as utilized by a standard evolutionary algorithm. Unlike traditional evolutionary algorithms and swarm intelligent algorithms, the iterative computation process of teaching–learning-based optimization is divided into two phases and each phase executes iterative learning operation. In this paper, we present a comprehensive survey on the recent advances in TLBO. A review of the current literature reveals intriguing challenges and suggests potential future research directions.
ISSN:	0925-2312
DOI:	10.1016/j.neucom.2023.126898