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  1. 1

    Modified Parameters of Harmony Search Algorithm for Better Searching by Nur Farraliza, Mansor, Abas, Z.A, Shibghatullah, A.S., Rahman, A.F.N.A

    Published 2017
    “…The harmony search algorithm is classified as a meta-heuristics algorithm that is capable of solving hard and combinatorial or discrete optimisation problems. …”
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  2. 2

    Enhancing harmony search parameters based on step and linear function for bus driver scheduling and rostering problems by Mansor, Nur Farraliza

    Published 2018
    “…Optimization is a major challenge in numerous practical world problems.According to the “No Free Lunch (NFL)” theorem,there is no existing single optimizer algorithm that is able to resolve all issues in an effective and efficient manner.It is varied and need to be solved according to the specific capabilities inherent to certain algorithms making it hard to foresee the algorithm that is best suited for each problem.As a result,the heuristic technique is adopted for this research as it has been identified as a potentially suitable algorithm.Alternative heuristic algorithms are also suggested to obtain optimal solutions with reasonable computational effort.However,the heuristic approach failed to produce a solution that nears optimum when the complexity of a problem increases;therefore a type of nature-inspired algorithm known as meta-euristics which utilises an intelligent searching mechanism over a population is considered and consequently used.The meta-heuristic approach is widely used to substitute heuristic terms and is broadly applied to address problems with regards to driver scheduling.However,this meta-heuristic technique is still unable to address the fairness issue in the scheduling and rostering problems.Hence,this research proposes a strategy to adopt an amendment of the harmony search algorithm in order to address the fairness issue which in turn will escalate the level of fairness in driver scheduling and rostering.The harmony search algorithm is classified as a meta-heuristics algorithm that is capable of solving hard and combinatorial or discrete optimisation problems.In this respect,the three main operators in harmony search,namely the Harmony Memory Consideration Rate (HMCR),Pitch Adjustment Rate (PAR) and Bandwidth (BW) play a vital role in balancing local exploitation and global exploration.These parameters influence the overall performance of the HS algorithm,and therefore it is crucial to fine-tune them. …”
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  3. 3

    Formulating and solving stochastic truck and trailer routing problems using meta-heuristic algorithms / Seyedmehdi Mirmohammadsadeghi by Seyedmehdi, Mirmohammadsadeghi

    Published 2015
    “…Therefore, multi-point simulated annealing (M-SA), memetic algorithm (MA) and tabu search (TS) algorithms are applied to solve the TTRPSD. …”
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  4. 4

    Automated-tuned hyper-parameter deep neural network by using arithmetic optimization algorithm for Lorenz chaotic system by Nurnajmin Qasrina Ann, ., Pebrianti, Dwi, Mohammad Fadhil, Abas, Bayuaji, Luhur

    Published 2023
    “…Deep neural networks (DNNs) are very dependent on their parameterization and require experts to determine which method to implement and modify the hyper-parameters value. This study proposes an automated-tuned hyper-parameter for DNN using a metaheuristic optimization algorithm, arithmetic optimization algorithm (AOA). …”
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  5. 5

    Impact of initialization of a modified particle swarm optimization on cooperative source searching by Ab. Majid, Mad Helmi, Arshad, Mohd Rizal, Yahya, Mohd Faid, Ibrahim, Abu Bakar

    Published 2023
    “…The findings shown that the proposed PSO model successfully reduce the target overshooting by choosing optimal PSO parameters and has better convergence rate and success rate compared to the benchmark algorithms. …”
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  6. 6

    Automated-tuned hyper-parameter deep neural network by using arithmetic optimization algorithm for Lorenz chaotic system by Ayop Azmi, Nurnajmin Qasrina Ann, Pebrianti, Dwi, Abas, Mohammad Fadhil, Bayuaji, Luhur

    Published 2023
    “…Deep neural networks (DNNs) are very dependent on their parameterization and require experts to determine which method to implement and modify the hyper-parameters value. This study proposes an automated-tuned hyper�parameter for DNN using a metaheuristic optimization algorithm, arithmetic optimization algorithm (AOA). …”
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  7. 7

    Genetic algorithm-based optimal overcurrent relays coordination for standalone sustainable hydrokinetic renewable energy distribution network by Ahmad, Saiful Zuhaimi

    Published 2019
    “…Thus, the objective of this work is to employ Genetic Algorithm (GA) technique in Matlab/Simulink for optimal overcurrent coordination and settings among all OCRs in the SHRE-DN in order to improve the speed of OCR tripping operation. …”
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  8. 8

    Machine learning for mapping and forecasting poverty in North Sumatera: a datadriven approach by Marpaung, Faridawaty, Ramadhani, Fanny, Dinata, Dewan

    Published 2024
    “…Thus, there were three poverty clusters - low, medium, and high - that were used in the model. The best model was created using the grid search cross-validation, while the best prediction results were created using the RF algorithm, with the following parameters: n-estimator = 50, max depth = 10, min samples split = 2, and min samples leaf = 1. …”
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  9. 9

    Distributed joint power control, beamforming and spectrum leasing for cognitive two-way relay networks by Iranpanah, Havzhin

    Published 2017
    “…In the first part of the thesis, distributed power control and beamforming algorithm is proposed in which users operating in the underlay mode can strategically adapt their power levels and maximize their own utilities. …”
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  10. 10
  11. 11

    Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decisio... by Daba, Layth Muwafaq Abdulhussein

    Published 2023
    “…Unlike the existing optimization algorithm, VL-WIDE features the capability of searching different lengths of solutions to cover the variable number of cloudlets for deployment. …”
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  12. 12

    Hospital site suitability assessment using three machine learning approaches: evidence from the Gaza strip in Palestine by Almansi, Khaled Yousef, Mohamed Shariff, Abdul Rashid, Abdullah, Ahmad Fikri, Syed Ismail, Sharifah Norkhadijah

    Published 2021
    “…Identification of the most significant parameters (conditioning factors) that influence a suitable hospital location was achieved by employing correlation-based feature selection (CFS) with the search algorithm (greedy stepwise). …”
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  13. 13

    Optimized techniques for landslide detection and characteristics using LiDAR data by Mezaal, Mustafa Ridha

    Published 2018
    “…In this task, two neural network algorithms, Recurrent Neural Networks (RNN) and Multi-Layer Perceptron Neural Networks (MLP-NN) were used and the hyper-parameters of the network architecture was optimized based on a systematic grid search. …”
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  14. 14

    A new HMCR parameter of harmony search for better exploration by Mansor, N.F., Abas, Z.A, Rahman, A.F.N.A, Shibghatullah, A.S., Sidek, S.

    Published 2016
    “…However, when performing a local search, the harmony search algorithm can be easily trapped in the local optima. …”
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  15. 15

    A new HMCR parameter of harmony search for better exploration by Nur Farraliza, Mansor, Abas, Z.A, Rahman, A.F.N.A, Shibghatullah, A.S., Sidek, S

    Published 2015
    “…However, when performing a local search, the harmony search algorithm can be easily trapped in the local optima. …”
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  16. 16

    A Hybrid Least Squares Support Vector Machine with Bat and Cuckoo Search Algorithms for Time Series Forecasting by Mohammed, Athraa Jasim, Ghathwan, Khalil Ibrahim, Yusof, Yuhanis

    Published 2020
    “…Pre-determining the values of parameters will affect the results of the forecasting model; hence, to find the optimal value of these parameters, this study investigates the adaptation of Bat and Cuckoo Search algorithms to optimize LSSVM parameters. …”
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  17. 17

    A modified crow search algorithm with niching technique for numerical optimization by Islam, J., Vasant, P.M., Negash, B.M., Watada, J.

    Published 2019
    “…The primitive crow search algorithm is a newly developed population-based algorithm which gained attention from the researchers of many fields as it needs only one parameter to be tuned. …”
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  18. 18

    A modified crow search algorithm with niching technique for numerical optimization by Islam, J., Vasant, P.M., Negash, B.M., Watada, J.

    Published 2019
    “…The primitive crow search algorithm is a newly developed population-based algorithm which gained attention from the researchers of many fields as it needs only one parameter to be tuned. …”
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  19. 19

    Taguchi-Grey Relational Analysis Method for Parameter Tuning of Multi-objective Pareto Ant Colony System Algorithm by Muthana, Shatha Abdulhadi, Ku Mahamud, Ku Ruhana

    Published 2023
    “…In any metaheuristic, the parameter values strongly affect the efficiency of an algorithm’s search. …”
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  20. 20

    A mild steel shear zone temperature minimization using genetic algorithm and direct search toolbox in cnc turning operation by Minhat, Mohamad, Abd. Rahman, Md Nizam

    Published 2013
    “…The upper and lower boundaries of cutting parameters will be used as operation constraints. There are many cutting parameters have a huge effect on the shear zone temperature while another have a low.…”
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