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  1. 1
    Review of the grey wolf optimization algorithm: variants and applications

    Review of the grey wolf optimization algorithm: variants and applications by Liu, Yunyun, As’arry, Azizan, Hassan, Mohd Khair, Hairuddin, Abdul Aziz

    Published 2023
    “…One of the most widely referenced Swarm Intelligence (SI) algorithms is the Grey Wolf Optimizer (GWO), which is based on the pack hunting and natural leadership organization of grey wolves. …”
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  2. 2
    Review of the grey wolf optimization algorithm: variants and applications

    Review of the grey wolf optimization algorithm: variants and applications by Liu, Yunyun, As’arry, Azizan, Hassan, Mohd Khair, Hairuddin, Abdul Aziz, Mohamad, Hesham

    Published 2024
    “…One of the most widely referenced Swarm Intelligence (SI) algorithms is the Grey Wolf Optimizer (GWO), which is based on the pack hunting and natural leadership organization of grey wolves. …”
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  3. 3
    A Modified Simulated Kalman Filter Optimizer with State Measurement, Substitution Mutation, Hamming Distance Calculation, and 2-Opt Operator

    A Modified Simulated Kalman Filter Optimizer with State Measurement, Substitution Mutation, Hamming Distance Calculation, and 2-Opt Operator by Suhazri Amrin, Rahmad, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

    Published 2021
    “…This paper presents modifications to measurement and estimation in SKF to accommodate the discrete search space. The modified algorithm is called Discrete Simulated Kalman Filter Optimizer (DSKFO). …”
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  4. 4
    A Modified Simulated Kalman Filter Optimizer with State Measurement, Substitution Mutation, Hamming Distance Calculation, and Swap Operator

    A Modified Simulated Kalman Filter Optimizer with State Measurement, Substitution Mutation, Hamming Distance Calculation, and Swap Operator by Suhazri Amrin, Rahmad, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

    Published 2021
    “…The simulated Kalman filter (SKF) is an algorithm for population-based optimization based on the Kalman filter framework. …”
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  5. 5
    Modified multi-verse optimizer for solving numerical optimization problems

    Modified multi-verse optimizer for solving numerical optimization problems by Jui, Julakha Jahan, Mohd Ashraf, Ahmad, Muhammad Ikram, Mohd Rashid

    Published 2020
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  6. 6
    Comparative study of modified BFGS and new scale modified BFGS for solving unconstrained optimization / Shahirah Atikah Mohamad Husnin

    Comparative study of modified BFGS and new scale modified BFGS for solving unconstrained optimization / Shahirah Atikah Mohamad Husnin by Mohamad Husnin, Shahirah Atikah

    Published 2018
    “…This indicated that the new scaled mBFGS algorithm performance is better than mBFGS algorithms.…”
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  7. 7
    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures

    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

    Published 2020
    “…For these reasons, to improve the time and accuracy of the coverage in population-based meta-heuristics and their utilization in HPAs, this thesis presents a novel optimization algorithm called the Raccoon Optimization Algorithm (ROA). …”
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  8. 8
    A modified crow search algorithm with niching technique for numerical optimization

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

    Published 2019
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  9. 9
    A modified crow search algorithm with niching technique for numerical optimization

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

    Published 2019
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  10. 10
    Performance Comparison of Parallel Bees Algorithm on Rosenbrock Function

    Performance Comparison of Parallel Bees Algorithm on Rosenbrock Function by Hammash, Nayif Mohammed

    Published 2012
    “…This thesis presents the parallel Bees Algorithm as a new approach for optimizing the last results for the Bees Algorithm. …”
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  11. 11
    Parallel distributed computational microcontroller system for adaptive antenna downlink transmitter power optimization

    Parallel distributed computational microcontroller system for adaptive antenna downlink transmitter power optimization by Sankar K.P., Tiong S.K., Koh S.P.J.

    Published 2023
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  12. 12
    Memoryless modified symmetric rank-one method for large-scale unconstrained optimization

    Memoryless modified symmetric rank-one method for large-scale unconstrained optimization by Modarres, Farzin, Abu Hassan, Malik, Leong, Wah June

    Published 2009
    “…In this study, we present a scaled memoryless modified Symmetric Rank-One (SR1) algorithm and investigate the numerical performance of the proposed algorithm for solving large-scale unconstrained optimization problems. …”
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  13. 13
    Design and implemtation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayyawi

    Design and implemtation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayyawi by Jabbar Hayyawi, Mustafa

    Published 2016
    “…Performance indices such as workspace, dexterity and stiffness, of the parallel manipulator are studied. The parallel manipulator is optimized based on the performance indices to obtain on the optimal design parameters for achieved maximum performance of the parallel manipulator. …”
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  14. 14
    Simulated kalman filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem

    Simulated kalman filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem by Suhazri Amrin, Rahmad, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

    Published 2022
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  15. 15
    Optimization of travelling salesman problem with precedence constraint using modified GA encoding

    Optimization of travelling salesman problem with precedence constraint using modified GA encoding by M. F. F., Ab Rashid, N. M. Zuki, N. M., F. R. M., Romlay, M., Jusop

    Published 2018
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  16. 16
    A modified n-th section line search in conjugate gradient methods for solving unconstrained optimization / Muhammad Imza Fakhri Jinudin

    A modified n-th section line search in conjugate gradient methods for solving unconstrained optimization / Muhammad Imza Fakhri Jinudin by Jinudin, Muhammad Imza Fakhri

    Published 2018
    “…Numerical results show that modified 6th section is the best method in term of number of iterations while modified 4th section is the best based on CPU times. …”
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  17. 17
    Identification of continuous-time model of hammerstein system using modified multi-verse optimizer

    Identification of continuous-time model of hammerstein system using modified multi-verse optimizer by Most. Julakha, Jahan Jui

    Published 2021
    “…his thesis implements a novel nature-inspired metaheuristic optimization algorithm, namely the modified Multi-Verse Optimizer (mMVO) algorithm, to identify the continuous-time model of Hammerstein system. …”
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  18. 18
    A review of genetic algorithms and parallel genetic algorithms on Graphics Processing Unit (GPU)

    A review of genetic algorithms and parallel genetic algorithms on Graphics Processing Unit (GPU) by Mohd Johar, Fauzi, Azmin, Farah Ayuni, Suaidi, Mohd Kadim, Shibghatullah, Abdul Samad, Ahmad, Badrul Hisham, Salleh, Siti Nadzirah, Abdul Aziz, Mohd Zainol Abidin, Md Shukor, Mahfuzah

    Published 2013
    “…Genetic Algorithms (GAs) is proven to be effective in solving many optimization tasks. …”
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  19. 19
    Voting algorithms for large scale fault-tolerant systems

    Voting algorithms for large scale fault-tolerant systems by Karimi, Abbas

    Published 2011
    “…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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  20. 20
    Modified quasi-Newton type methods using gradient flow system for solving unconstrained optimization

    Modified quasi-Newton type methods using gradient flow system for solving unconstrained optimization by Yap, Chui Ying

    Published 2016
    “…Numerical results are established to demonstrate the efficiency of our modified methods. …”
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