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    Enhanced gravitational search algorithm for nano-process parameter optimization problem / Norlina Mohd Sabri by Mohd Sabri, Norlina

    Published 2020
    “…Based on the capabilities of the metaheuristic algorithms, this research is proposing the enhanced Gravitational Search Algorithm (eGSA) to solve the nano-process parameter optimization problem. …”
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    Thesis
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    Fuzzy adaptive emperor penguin optimizer for global optimization problems by Md Abdul, Kader

    Published 2023
    “…The respective solution results of the competing metaheuristic algorithms were compared. The experimental results demonstrate that FAEPO significantly improved the performance especially of its predecessor (EPO), an improved variant of EPO (i.e., IEPO), and a fuzzy-based variant of ChOA (i.e., FChOA) and gives superior performance against the competing metaheuristic algorithms. …”
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    Thesis
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    Elitism Based Migrating Birds Optimization Algorithm for Optimization Testing by Hasneeza, L. Zakaria, Kamal Z., Zamli

    Published 2017
    “…This proposed strategy is the first to utilize population based metaheuristic algorithm i.e. MBO with elitism for solving CIT problem. …”
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    Article
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    PMT : opposition based learning technique for enhancing metaheuristic algorithms performance by Hammoudeh, S. Alamri

    Published 2020
    “…Metaheuristic algorithms have shown promising performance in solving sophisticated real-world optimization problems. …”
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    Thesis
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    Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction by Zuriani, Mustaffa

    Published 2014
    “…This study proposed a hybrid algorithm, based on Artificial Bee Colony (ABC) and LSSVM, that consists of three algorithms; ABC-LSSVM, lvABC-LSSVM and cmABC-LSSVM. …”
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    Thesis
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    A New Optimization Algorithm based on Copulation Behavior of Simine Jackals by Alemu Lemma, Tamiru, Mohd Hashim, Fakhruldin

    Published 2011
    “…This work introduces a new meta-heuristic algorithm, termed as Simine Jackal algorithm, designed to solve optimization problems. …”
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    Conference or Workshop Item
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