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  1. 1
    A Comparative Study on three Component Selection Mechanisms for Hyper-Heuristics in Expensive Optimization

    A Comparative Study on three Component Selection Mechanisms for Hyper-Heuristics in Expensive Optimization by Jia Hui Ong, Jason Teo

    Published 2018
    “…The performance of hyper-heuristics is highly encouraging against a specifically tailored algorithm for CEC test set of expensive optimization problems.…”
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  2. 2
    Design Of Perturbative Hyper-Heuristics For Combinatorial Optimisation

    Design Of Perturbative Hyper-Heuristics For Combinatorial Optimisation by Choong, Shin Siang

    Published 2019
    “…The use of a single LLH leads to poor performance when the particular heuristic is incompetent in solving the problem. …”
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  3. 3
    HEURISTIC OPTIMIZATION OF BAT ALGORITHM FOR HETEROGENEOUS SWARMS USING PERCEPTION

    HEURISTIC OPTIMIZATION OF BAT ALGORITHM FOR HETEROGENEOUS SWARMS USING PERCEPTION by Kappagantula, S., Vojjala, S., Iyer, A.A., Velidi, G., Emani, S., Vandrangi, S.K.

    Published 2023
    “…In this paper, we study the advantages of fusing the Meta-Heuristic Bat Algorithm with Heuristic Optimization. …”
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  4. 4
    Hybrid ant colony optimization algorithm for container loading problem

    Hybrid ant colony optimization algorithm for container loading problem by Yap, Ching Nei

    Published 2012
    “…In this study, a Tower Building (TB) heuristic with less complexity, inspired by the stack building heuristic, is proposed to hybridize with an Ant Colony Optimization (ACO) for solving the Container Loading Problem (CLP). …”
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  5. 5
    Development of heuristic task scheduling algorithm in cloud computing

    Development of heuristic task scheduling algorithm in cloud computing by Diallo, Laouratou, Hassan Abdalla Hashim, Aisha, Olanrewaju, Rashidah Funke

    Published 2016
    “…Therefore, heuristics algorithms are widely proposed recently for their capabilities of resources optimization in a range finite of time. …”
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    Proceeding Paper
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  6. 6
    Enhancing generality of meta-heuristic algorithms through adaptive selection and hybridization

    Enhancing generality of meta-heuristic algorithms through adaptive selection and hybridization by Kamal Z., Zamli

    Published 2018
    “…Many meta-heuristic algorithms have been developed to date (e.g. …”
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  7. 7
    Optimal power flow with renewable power generations using hyper-heuristic technique

    Optimal power flow with renewable power generations using hyper-heuristic technique by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

    Published 2024
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  8. 8
    A hyper-heuristic based strategy for image segmentation using multilevel thresholding

    A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, Fakhrud Din, Shah Khalid, Kamal Zuhairi Zamli, Aftab Alam

    Published 2025
    “…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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  9. 9
    Ant colony optimization algorithm for dynamic scheduling of jobs in computational grid

    Ant colony optimization algorithm for dynamic scheduling of jobs in computational grid by Ku-Mahamud, Ku Ruhana, Ramli, Razamin, Yusof, Yuhanis, Mohamed Din, Aniza, Mahmuddin, Massudi

    Published 2012
    “…Job scheduling problem is classified as an NP-hard problem.Such a problem can be solved only by using approximate algorithms such as heuristic and meta-heuristic algorithms.Among different optimization algorithms for job scheduling, ant colony system algorithm is a popular meta-heuristic algorithm which has the ability to solve different types of NP-hard problems.However, ant colony system algorithm has a deficiency in its heuristic function which affects the algorithm behavior in terms of finding the shortest connection between edges.This research focuses on a new heuristic function where information about recent ants’ discoveries has been considered.The new heuristic function has been integrated into the classical ant colony system algorithm.Furthermore, the enhanced algorithm has been implemented to solve the travelling salesman problem as well as in scheduling of jobs in computational grid.A simulator with dynamic environment feature to mimic real life application has been development to validate the proposed enhanced ant colony system algorithm. …”
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  10. 10
    Optimizing the placement of fire department in Kulim using greedy heuristic and simplex method / Muhammad Abu Syah Mohd Suzaly

    Optimizing the placement of fire department in Kulim using greedy heuristic and simplex method / Muhammad Abu Syah Mohd Suzaly by Mohd Suzaly, Muhammad Abu Syah

    Published 2023
    “…The first method is greedy heuristic method. Greedy heuristics is a type of optimization algorithm that makes decisions based on locally optimal solutions. …”
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  11. 11
    A hyper-heuristic based strategy for image segmentation using multilevel thresholding

    A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, ., Fakhrud, Din, Shah, Khalid, Kamal Z., Zamli, Alam, Aftab

    Published 2025
    “…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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  12. 12
    Performance evaluation of task scheduling using hybrid meta-heuristic in the heterogeneous cloud environment

    Performance evaluation of task scheduling using hybrid meta-heuristic in the heterogeneous cloud environment by Mohammed, Faten Ameen Saif

    Published 2019
    “…Thus, this study focuses on optimizing the hybrid meta-heuristic (genetic algorithm along with DE algorithm that minimizes the completion time and enhances the performance of the task scheduling. …”
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  13. 13
    Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data

    Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data by Qadir Saraf, Tara Othman, Fuad, Norfaiza, Md Taujuddin, Nik Shahidah Afifi

    Published 2023
    “…Feature Selection in High Dimensional Space is a combinatory optimization problem with an NP-hard nature. Meta-heuristic searching with embedding information theory-based criteria in the fitness function for selecting the relevant features is used widely in current feature selection algorithms. …”
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  14. 14
    Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data

    Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data by Qadir Saraf, Tara Othman, Fuad, Norfaiza, Md Taujuddin, Nik Shahidah Afifi

    Published 2023
    “…Feature Selection in High Dimensional Space is a combinatory optimization problem with an NP-hard nature. Meta-heuristic searching with embedding information theory-based criteria in the fitness function for selecting the relevant features is used widely in current feature selection algorithms. …”
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  15. 15
    Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data

    Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data by Qadir Sara, Tara Othman, Fuad, Norfaiza, Md Taujuddin, Nik Shahidah Afifi

    Published 2023
    “…Feature Selection in High Dimensional Space is a combinatory optimization problem with an NP-hard nature. Meta-heuristic searching with embedding information theory-based criteria in the fitness function for selecting the relevant features is used widely in current feature selection algorithms. …”
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  16. 16
    Optimal placement and sizing of battery energy storage system for losses reduction using whale optimization algorithm

    Optimal placement and sizing of battery energy storage system for losses reduction using whale optimization algorithm by Wong L.A., Ramachandaramurthy V.K., Walker S.L., Taylor P., Sanjari M.J.

    Published 2023
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  17. 17
    Comparative Performance Analysis of Bat Algorithm and Bacterial Foraging Optimization Algorithm using Standard Benchmark Functions

    Comparative Performance Analysis of Bat Algorithm and Bacterial Foraging Optimization Algorithm using Standard Benchmark Functions by Mazlina, Abdul Majid, Alsariera, Yazan A., Alamri, Hammoudeh S., Nasser, Abdullah M., Kamal Z., Zamli

    Published 2014
    “…Over the last 30 years, many meta-heuristic algorithms have been developed in the literature including that of Simulated Annealing (SA), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Harmony Search Algorithm (HS) to name a few. …”
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  18. 18
    Dynamic social behavior algorithm for real-parameter optimization problems and optimization of hyper beamforming of linear antenna arrays

    Dynamic social behavior algorithm for real-parameter optimization problems and optimization of hyper beamforming of linear antenna arrays by Prajindra�Sankar K., Kiong T.S., Siaw�Paw J.K.

    Published 2023
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  19. 19
    Studying the effect of training Levenberg Marquardt neural network by using hybrid meta-heuristic algorithms

    Studying the effect of training Levenberg Marquardt neural network by using hybrid meta-heuristic algorithms by Abubakar, Adamu, Khan, Abdullah, Nawi, Nazri Mohd, Rehman, M. Z., Teh , Ying Wah, Chiroma , Haruna, Herawan, Tutut

    Published 2016
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  20. 20
    Comparative study of meta-heuristics optimization algorithm using benchmark function

    Comparative study of meta-heuristics optimization algorithm using benchmark function by Ismail, I., Halim, A.H.

    Published 2017
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