Teaching-Learning-Based Optimization: An optimization method for continuous non-linear large scale problems

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Artificial Intelligence (AI) Methods in Optical Networks: A Comprehensive Survey (2018, methodology): “However, when some of the conditions previously mentioned are relaxed, or when the network size prohibits the use of the former techniques, those methods have been complemented or replaced by local search algorithms and metaheuristics like simulated annealing, genetic algorithms, swarm optimization,”
Truss topology optimization with static and dynamic constraints using modified subpopulation teaching–learning-based optimization (2016, methodology): “The functioning of the TLBO algorithm is divided into two phases, the ‘teacher phase’ and the ‘learner phase’ (Rao, Savsani, and Vakharia 2011, 2012).”
A comprehensive survey on recent metaheuristics for feature selection (2022, background): “The algorithm has gained attention with respect to its rapid convergence and the lack of algorithmic parameters [201, 202].”
Parameter optimization of modern machining processes using teaching-learning-based optimization algorithm (2013, neutral): “[30, 31].”