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  1. 1
    Estimation-based Metaheuristics: A New Branch of Computational Intelligence

    Estimation-based Metaheuristics: A New Branch of Computational Intelligence by Nor Hidayati, Abd Aziz, Zuwairie, Ibrahim, Saifudin, Razali, Nor Azlina, Ab. Aziz

    Published 2016
    “…In this paper, a new branch of computational intelligence named estimation-based metaheuristic is introduced. Metaheuristic algorithms can be classified based on their source of inspiration. …”
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  2. 2
    Formulation of metaheuristic algorithms based on artificial bee colony for engineering problems

    Formulation of metaheuristic algorithms based on artificial bee colony for engineering problems by Lee, Wei Wen

    Published 2024
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  3. 3
    Simulated Kalman Filter: A Novel Estimation-based Metaheuristic Optimization Algorithm

    Simulated Kalman Filter: A Novel Estimation-based Metaheuristic Optimization Algorithm by Zuwairie, Ibrahim, Nor Hidayati, Abd Aziz, Nor Azlina, Ab. Aziz, Saifudin, Razali, Mohd Saberi, Mohamad

    Published 2016
    “…In this paper, a new population-based metaheuristic optimization algorithm, named Simulated Kalman Filter (SKF) is introduced. …”
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  4. 4
    PMT : opposition based learning technique for enhancing metaheuristic algorithms performance

    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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  5. 5
    Iteration strategy and ts effect towards the performance of population based metaheuristics

    Iteration strategy and ts effect towards the performance of population based metaheuristics by Nor Azlina, Ab. Aziz, Nor Hidayati, Abdul Aziz, Azlan, Abd Aziz, Tasiransurini, Abdul Rahman, Wan Zakiah, Wan Ismail, Zuwairie, Ibrahim

    Published 2020
    “…The algorithms can be categorized based on number of agents, either single agent algorithms which are also known as single solution metaheuristics or multi agents algorithms, also known as population-based metaheuristics. …”
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  6. 6
    On the exploration and exploitation in popular swarm-based metaheuristic algorithms

    On the exploration and exploitation in popular swarm-based metaheuristic algorithms by Hussain, Kashif, Mohd Salleh, Mohd Najib, Cheng, Shi, Shi, Yuhui

    Published 2018
    “…This study, therefore, performed in-depth empirical analysis by quantitatively analyzing exploration and exploitation of five swarm-based metaheuristic algorithms. The analysis unearthed explanations the way algorithms performed on numerical problems as well as on real-world application of classification using adaptive neuro-fuzzy inference system (ANFIS) trained by selected metaheuristics. …”
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  7. 7
    Overview of metaheuristic: classification of population and trajectory

    Overview of metaheuristic: classification of population and trajectory by Zainul Rashid, Zarina

    Published 2010
    “…An algorithm that applies a metaheuristic method is used when there are no specific methods to find a solution. …”
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  8. 8
    Performances Of Metaheuristic Algorithms In Optimizing Tool Capacity Allocations

    Performances Of Metaheuristic Algorithms In Optimizing Tool Capacity Allocations by Goheannee

    Published 2014
    “…In this research, the algorithms studied includes Genetic Algorithm, Particle Swarm Optimization Algorithm, Differential Evolution Algorithm, Harmony Search Algorithm, Teaching-LearningBased Optimization Algorithm and Black Hole Algorithm. …”
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  9. 9
    Advances of metaheuristic algorithms in training neural networks for industrial applications

    Advances of metaheuristic algorithms in training neural networks for industrial applications by Chong H.Y., Yap H.J., Tan S.C., Yap K.S., Wong S.Y.

    Published 2023
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  10. 10
    Hybrid metaheuristics for QOS-aware service composition / Hadi Naghavipour

    Hybrid metaheuristics for QOS-aware service composition / Hadi Naghavipour by Hadi , Naghavipour

    Published 2022
    “…An absolute majority of base algorithms for this problem were nature-inspired and population-based metaheuristics extended to complementary methods in hybrid solutions. …”
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  11. 11
    Adaptive beamforming algorithm based on Simulated Kalman Filter

    Adaptive beamforming algorithm based on Simulated Kalman Filter by Kelvin Lazarus, Lazarus

    Published 2017
    “…Some of the metaheuristic algorithms have been modified from the original algorithms to improve the algorithms performance in adaptive beamforming application. …”
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  12. 12
    Optimal placement and sizing of FACTS devices for optimal power flow using metaheuristic optimizers

    Optimal placement and sizing of FACTS devices for optimal power flow using metaheuristic optimizers by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

    Published 2022
    “…OPF is one of the well-known problems in power system operations and with the inclusion of the FACTS devices allocation problems into OPF will make the solution more complex. Thus, seven metaheuristic algorithms: Barnacles Mating Optimizer (BMO), Marine Predators Algorithm (MPA), Moth–Flame Optimization (MFO), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Teaching–Learning-Based Optimization (TLBO) and Heap-Based Optimizer (HBO) are used to solve two objective functions: power loss and cost minimizations. …”
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  13. 13
    Metaheuristic searching genetic algorithm based reliability assessment of hybrid power generation system

    Metaheuristic searching genetic algorithm based reliability assessment of hybrid power generation system by Abdalla, Ahmed N., Nazir, Muhammad Shahzad, Ming, Xin Jiang, Kadhem, Athraa Ali, Abdul Wahab, Noor Izzri, Suqun, Cao, Rendong, Ji

    Published 2020
    “…The MSGA is based on a combination of metaheuristic scanning and Genetic Algorithm. …”
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  14. 14
    A hybrid kidney algorithm strategy for combinatorial interaction testing problem

    A hybrid kidney algorithm strategy for combinatorial interaction testing problem by Ameen Ali, Mohammed Ba Homaid

    Published 2022
    “…In addition, the hybrid metaheuristic-based CIT strategies require more execution time than their own original algorithm-based strategies. …”
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  15. 15
    Tiki-taka algorithm: a novel metaheuristic inspired by football playing style

    Tiki-taka algorithm: a novel metaheuristic inspired by football playing style by Mohd Fadzil Faisae, Ab Rashid

    Published 2021
    “…The performance of the proposed algorithm was compared with 11 other metaheuristics from sport-based, highly cited and recent algorithms. …”
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  16. 16
    FPGA implementation of metaheuristic optimization algorithm

    FPGA implementation of metaheuristic optimization algorithm by Nurul Hazlina, Noordin, Phuah, Soon Eu, Zuwairie, Ibrahim

    Published 2023
    “…The selected metaheuristic was the Simulated Kalman Filter (SKF) which proposed an algorithm that was low in complexity and used a small number of steps. …”
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  17. 17
    Fpga Implementation Of Metaheuristic Optimization Algorithm

    Fpga Implementation Of Metaheuristic Optimization Algorithm by Phuah, Soon Eu

    Published 2022
    “…The selected metaheuristic was the Simulated Kalman Filter (SKF) which proposed an algorithm that was low in complexity and used a small number of steps. …”
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  18. 18
    Metaheuristics algorithms to identify nonlinear Hammerstein model: A decade survey

    Metaheuristics algorithms to identify nonlinear Hammerstein model: A decade survey by Jui, Julakha Jahan, Mohd Ashraf, Ahmad, Muhammad Ikram, Mohd Rashid

    Published 2022
    “…Various metaheuristics algorithms are being introduced on an annual basis and applications that are more new are gradually being discovered. …”
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  19. 19
    Hybrid Metaheuristic Algorithm and Metaheuristic Performance Measurement for Solving University Course Timetabling Problem

    Hybrid Metaheuristic Algorithm and Metaheuristic Performance Measurement for Solving University Course Timetabling Problem by Md Sultan, Abu Bakar

    Published 2007
    “…Acquiring the proper balance between intensification and diversification strategies is the crucial factor in obtaining an effective metaheuristic. This research focused on the implementation of an hybrid evolutionary metaheuristic namely Two_point Hybrid Evolutionary Algorithm (Tp_HEA) on university course timetabling problem instances (UCTP). …”
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  20. 20
    Metaheuristic Algorithm for university timetabling problem

    Metaheuristic Algorithm for university timetabling problem by Wahid, Juliana, Abdul Rahman, Syariza, Mohamed Din, Aniza

    Published 2021
    “…With huge number of curriculum and students, the introduction of base curriculum model and the use of metaheuristic algorithm would ease the curriculum-based timetabling process. …”
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