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A Q-Learning-Based Brainstorming Optimization Algorithm for Solving Multimodal Optimization Problems

by Cheng, Shi, Jin, Honglin, Lu, Hui, Shi, Yuhui
Published in IEEE transactions on consumer electronics (01.05.2025)

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An effective teaching–learning-based optimization algorithm for the flexible job-shop scheduling problem with fuzzy processing time

by Xu, Ye, Wang, Ling, Wang, Sheng-yao, Liu, Min
Published in Neurocomputing (Amsterdam) (19.01.2015)

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A trajectory-based algorithm enhanced by Q-learning and cloud integration for hybrid flexible flowshop scheduling problem with sequence-dependent setup times: A case study

by Ozsoydan, Fehmi Burcin
Published in Computers & operations research (01.09.2025)

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A novel learning algorithm based on computing the rules’ desired outputs of a TSK fuzzy neural network with non-separable fuzzy rules

by Salimi-Badr, Armin, Ebadzadeh, Mohammad Mehdi
Published in Neurocomputing (Amsterdam) (22.01.2022)

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An Improved Teaching-Learning-Based Optimization Algorithm with Reinforcement Learning Strategy for Solving Optimization Problems

by Wu, Di, Wang, Shuang, Liu, Qingxin, Abualigah, Laith, Jia, Heming
Published in Computational intelligence and neuroscience (24.03.2022)

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The ɛ-constraint as a learning strategy in the population-based algorithm: The case of Bi-Objective Obnoxious p-Median Problems

by Aïder, Méziane, Azzi, Aida-Ilham, Hifi, Mhand
Published in Knowledge-based systems (08.04.2023)

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Solving discounted {0-1} knapsack problems by a discrete hybrid teaching-learning-based optimization algorithm

by Wu, Congcong, Zhao, Jianli, Feng, Yanhong, Lee, Malrey
Published in Applied intelligence (Dordrecht, Netherlands) (01.06.2020)

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A gamified teaching–learning based optimization algorithm for a three-echelon supply chain scheduling problem in a two-stage assembly flow shop environment

by Rostami, Mohammad, Yousefzadeh, Ali
Published in Applied soft computing (01.10.2023)

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A self-learning whale optimization algorithm based on reinforcement learning for a dual-resource flexible job shop scheduling problem

by Manafi, Ehsan, Domenech, Bruno, Tavakkoli-Moghaddam, Reza, Ranaboldo, Matteo
Published in Applied soft computing (01.08.2025)

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Distributed Task Replication for Vehicular Edge Computing: Performance Analysis and Learning-Based Algorithm

by Sun, Yuxuan, Zhou, Sheng, Niu, Zhisheng
Published in IEEE transactions on wireless communications (01.02.2021)

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Enhanced grasshopper optimization algorithm using elite opposition-based learning for solving real-world engineering problems

by Yildiz, Betül Sultan, Pholdee, Nantiwat, Bureerat, Sujin, Yildiz, Ali Riza, Sait, Sadiq M.
Published in Engineering with computers (01.10.2022)

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Monitor system and Gaussian perturbation teaching–learning-based optimization algorithm for continuous optimization problems

by Shih, Po-Chou, Zhang, Yang, Zhou, Xizhao
Published in Journal of ambient intelligence and humanized computing (01.02.2022)

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Improved teaching-learning-based and JAYA optimization algorithms for solving flexible flow shop scheduling problems

by Buddala, Raviteja, Mahapatra, Siba Sankar
Published in Journal of industrial engineering international (01.09.2018)

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An improved teaching-learning-based optimization algorithm for numerical and engineering optimization problems

by Yu, Kunjie, Wang, Xin, Wang, Zhenlei
Published in Journal of intelligent manufacturing (01.08.2016)

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A chaotic teaching learning based optimization algorithm for clustering problems

by Kumar, Yugal, Singh, Pradeep Kumar
Published in Applied intelligence (Dordrecht, Netherlands) (01.03.2019)

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Mid-term electricity load forecasting by a new composite method based on optimal learning MLP algorithm

by Askari, Mostafa, Keynia, Farshid
Published in IET generation, transmission & distribution (13.03.2020)

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Deep reinforcement learning-based beam Hopping algorithm in multibeam satellite systems

by Hu, Xin, Liu, Shuaijun, Wang, Yipeng, Xu, Lexi, Zhang, Yuchen, Wang, Cheng, Wang, Weidong
Published in IET communications (08.10.2019)

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A hybrid teaching and learning-based optimization algorithm for distributed sand casting job-shop scheduling problem

by Tang, Hongtao, Fang, Bo, Liu, Rong, Li, Yibing, Guo, Shunsheng
Published in Applied soft computing (01.05.2022)

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A self-learning discrete salp swarm algorithm based on deep reinforcement learning for dynamic job shop scheduling problem

by Gu, Yiming, Chen, Ming, Wang, Liang
Published in Applied intelligence (Dordrecht, Netherlands) (01.08.2023)

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Solving Inverse Problems With Deep Neural Networks - Robustness Included?

by Genzel, Martin, Macdonald, Jan, Marz, Maximilian
Published in IEEE transactions on pattern analysis and machine intelligence (01.01.2023)

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