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  1. 1
    New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems

    New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems by Nor Shuhada, Ibrahim

    Published 2024
    “…The increasing interest among researchers in the application of metaheuristic algorithms for search optimization has resulted in notable progress, especially in tackling single objective optimization problems. …”
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  2. 2
    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
    “…Most metaheuristic algorithms are designed for continuous optimization problem. …”
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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
    “…The simulated Kalman filter (SKF) is an algorithm for population-based optimization based on the Kalman filter framework. …”
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  4. 4
    A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution

    A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution by Warid, Warid, Hizam, Hashim, Mariun, Norman, Abdul Wahab, Noor Izzri

    Published 2018
    “…This study introduces a novel meta-heuristic optimization algorithm known as quasi-oppositional modified Jaya (QOMJaya) to solve different multi-objective optimal power flow (MOOPF) problems. …”
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  5. 5
    A Modified Gravitational Search Algorithm for Discrete Optimization Problem

    A Modified Gravitational Search Algorithm for Discrete Optimization Problem by Zuwairie, Ibrahim, Zulkifli, Md. Yusof, Shahdan, Sudin, Sophan Wahyudi, Nawawi, Amar Faiz, Zainal Abidin, Muhammad Arif, Abdul Rahim, Kamal, Khalil

    Published 2014
    “…This paper presents a modified Gravitational Search Algorithm (GSA) called Discrete Gravitational Search Algorithm (DGSA) for discrete optimization problems. …”
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  6. 6
    Optimized clustering with modified K-means algorithm

    Optimized clustering with modified K-means algorithm by Alibuhtto, Mohamed Cassim

    Published 2021
    “…Besides, some real data sets were examined to validate the proposed algorithm. Empirical evidences based on simulated data sets indicated that the proposed modified k-means algorithm is able to recognise the optimum number of clusters for uncorrelated data sets. …”
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  7. 7
    Distance evaluated simulated kalman filter with state encoding for combinatorial optimization problems

    Distance evaluated simulated kalman filter with state encoding for combinatorial optimization problems by Yusof, Zulkifli Md., Ibrahim, Zuwairie, Adam, Asrul, Azmi, Kamil Zakwan Mohd, Ab. Rahman, Tasiransurini, Muhammad, Badaruddin, Ab. Aziz, Nor Azlina, Abd Aziz, Nor Hidayati, Mokhtar, Norrima, Shapiai, Mohd Ibrahim, Muhammad, Mohd Saberi

    Published 2018
    “…Simulated Kalman Filter (SKF) is a population-based optimization algorithm which exploits the estimation capability of Kalman filter to search for a solution in a continuous search space. …”
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  8. 8
    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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  9. 9
    Optimal power flow using the Jaya algorithm

    Optimal power flow using the Jaya algorithm by Warid, Warid, Hizam, Hashim, Mariun, Norman, Abdul Wahab, Noor Izzri

    Published 2016
    “…Unlike other population-based optimization methods, no algorithm-particular controlling parameters are required for this algorithm. …”
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  10. 10
    Development of optimization Alghorithm for uncertain non-linear dynamical system

    Development of optimization Alghorithm for uncertain non-linear dynamical system by Abdul Aziz, Mohd. Ismail, Yaacob, Nazeeruddin, Mohd. Said, Norfarizan, Hamzah, Nor Hazadura

    Published 2004
    “…Based on the results of these simulations, we compared the number of iterations needed by each algorithm to arrive at the optimal solution and the CPU time taken for each algorithm to execute the search. …”
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  11. 11
    Distance evaluated simulated kalman filter with state encoding for combinatorial optimization problems

    Distance evaluated simulated kalman filter with state encoding for combinatorial optimization problems by Zuwairie, Ibrahim, Zulkifli, Md. Yusof, Asrul, Adam, Kamil Zakwan, Mohd Azmi, Tasiransurini, Ab Rahman, Badaruddin, Muhammad, Nor Azlina, Ab. Aziz, Norrima, Mokhtar, Mohd Ibrahim, Shapiai, Mohd Saberi, Mohamad

    Published 2018
    “…Simulated Kalman Filter (SKF) is a population-based optimization algorithm which exploits the estimation capability of Kalman filter to search for a solution in a continuous search space. …”
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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
    “…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
    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
    “…Simulated Kalman Filter (SKF) solves optimization problems by finding the estimate of the optimum solution. …”
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  14. 14
    An improved electromagnetism-like algorithm for numerical optimization

    An improved electromagnetism-like algorithm for numerical optimization by Tan J.-D., Dahari M., Koh S.-P., Koay Y.-Y., Abed I.-A.

    Published 2023
    “…Algorithms; Benchmarking; Global optimization; Iterative methods; Nonlinear equations; Probes; Bench-mark problems; Computational simulation; Electromagnetism-like algorithm; Electromagnetism-like mechanism algorithms; Electromagnetism-like mechanisms; Metaheuristic; Numerical optimizations; Split-Probe-Compare; Optimization…”
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  15. 15
    An application of teaching–learning-based optimization for solving the optimal power flow problem with stochastic wind and solar power generators

    An application of teaching–learning-based optimization for solving the optimal power flow problem with stochastic wind and solar power generators by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Muhammad Ikram, Mohd Rashid

    Published 2023
    “…This paper proposes the implementation of metaheuristic algorithm namely, teaching–learning-based optimization (TLBO) algorithm to solve optimal power flow (OPF) problem. …”
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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
    “…These line search methods are tested based on six standard optimization test problems. …”
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  17. 17
    Using Metaheuristics Algorithms (MHAs) to Optimize Water Supply Operation in Reservoirs: a Review

    Using Metaheuristics Algorithms (MHAs) to Optimize Water Supply Operation in Reservoirs: a Review by Almubaidin M.A.A., Ahmed A.N., Sidek L.B.M., Elshafie A.

    Published 2023
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  18. 18
    An experimental study of neighbourhood based metaheuristic algorithms for test case generation satisfying the modified condition / decision coverage criterion

    An experimental study of neighbourhood based metaheuristic algorithms for test case generation satisfying the modified condition / decision coverage criterion by Haque, Ariful

    Published 2018
    “…We have chosen four neighborhood based algorithms which are commonly used in optimization problems and divided them in newly implemented and re-implemented category. …”
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  19. 19
    Artificial Immune System Based Remainder Method for Multimodal Mathematical Function Optimization

    Artificial Immune System Based Remainder Method for Multimodal Mathematical Function Optimization by Yap, David F. W., Koh, S. P., Tiong, S. K.

    Published 2011
    “…Conversely, Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO) have been used efficiently in solving complex optimization problems, but they have an inclination to converge prematurely. …”
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  20. 20
    Antibody Remainder Method Based Artificial Immune System for Mathematical Function Optimization

    Antibody Remainder Method Based Artificial Immune System for Mathematical Function Optimization by Yap, David F. W., Koh, S. P., Tiong, S. K.

    Published 2011
    “…Artificial immune system (AIS) is one of the natureinspired algorithm for solving optimization problem. In AIS, clonal selection algorithm (CSA) is able to improve global searching ability. …”
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