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  1. 1

    Optimal power flow based on fuzzy linear programming and modified Jaya algorithms by Alzihaymee, Warid Sayel Warid

    Published 2017
    “…A set of modified and novel optimization algorithms are proposed in this thesis to deal with different single and multi-objective OPF problems. …”
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    Thesis
  2. 2

    Methodology for modified whale optimization algorithm for solving appliances scheduling problem by Omar, Mohd Faizal, Mohd Bakeri, Noorhadila, Mohd Nawi, Mohd Nasrun, Hairani, Norfazlirda, Khalid, Khalizul

    Published 2020
    “…Whale Optimization Algorithm (WOA) is considered as one of the newest metaheuristic algorithms to be used for solving a type of NP-hard problems. …”
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    Article
  3. 3

    Normative Fish Swarm Algorithm For Global Optimization With Applications by Tan, Weng Hooi

    Published 2019
    “…Artificial Fish Swarm Algorithm (AFSA) have become popular optimization technique used to solve various problems, Nevertheless, according to surveys, the existing fish swarm algorithms still have some deficiencies to strike the exact optimum within appropriate convergence rate. …”
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    Thesis
  4. 4

    Optimization of chemotherapy using metaheuristic optimization algorithms / Prakas Gopal Samy by Prakas Gopal , Samy

    Published 2024
    “…Advancing multi-objective optimization techniques for cancer treatment strategies, the study strategically incorporates Swarm Intelligence (SI) and Evolutionary Algorithms (EA). …”
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    Thesis
  5. 5

    Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems by Zulkifli, Munierah, Abd Rahmin, Nor Aliza, Wah, June Leong

    Published 2023
    “…Stochastic gradient descent (SGD) is one of the most common algorithms used in solving large unconstrained optimization problems. …”
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    Article
  6. 6

    Hybridization of modified sine cosine algorithm with tabu search for solving quadratic assignment problem by Nurdiyana, Jamil

    Published 2022
    “…Sine Cosine Algorithm (SCA) is a population-based metaheuristic method that widely used to solve various optimization problem due to its ability in stabilizing between exploration and exploitation. …”
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    Thesis
  7. 7

    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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    Article
  8. 8

    HYBRID SINE COSINE AND FITNESS DEPENDENT OPTIMIZER FOR INCOMPLETE DATASET by Chiu, Po Chan, Ali, Selamat, Kuok, King Kuok

    Published 2024
    “…The modifications include a modified pace-updating equation, a random weight factor and global fitness weight strategy, a conversion parameter strategy, and a best solution-updating strategy. …”
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    Book Chapter
  9. 9

    Hybrid evolutionary optimization algorithms: A case study in manufacturing industry by Vasant, P.

    Published 2014
    “…This membership function is applied for its useful performance through industrial production problems by employing hybrid evolutionary optimization algorithms. …”
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    Book
  10. 10

    Spread enhancement for firefly algorithm with application to control mechanism of exoskeleton system by Kasdirin, Hyreil Anuar, Ali, Siti Khadijah, Tokhi, M. O.

    Published 2019
    “…Firefly algorithm (FA) is a swarm intelligence based algorithm for global optimization and has widely been used in solving problems in many areas. …”
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    Article
  11. 11

    Variable Neighborhood Descent and Whale Optimization Algorithm for Examination Timetabling Problems at Universiti Malaysia Sarawak by Emily Sing Kiang, Siew

    Published 2025
    “…A constructive algorithm was developed to generate an initial feasible solution, which was subsequently refined using two primary approaches to evaluate their efficiency: Iterative Threshold Pipe Variable Neighborhood Descent (IT-PVND), and a modified Whale Optimization Algorithm (WOA). …”
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    Thesis
  12. 12

    An Adaptive Switching Cooperative Source Searching And Tracing Algorithms For Underwater Acoustic Source Localization by Majid, Mad Helmi Ab.

    Published 2019
    “…Secondly, to trace the source to its approximate location, a Source Tracing Algorithm (STA) known as an Asynchronous Dynamically Adjustable Particle Swarm Optimization (ADAPSO) is suggested. …”
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    Thesis
  13. 13

    An hour ahead electricity price forecasting with least square support vector machine and bacterial foraging optimization algorithm by Razak I.A.W.A., Abidin I.Z., Siah Y.K., Abidin A.A.Z., Rahman T.K.A., Baharin N., Jali M.H.B.

    Published 2023
    “…Therefore, a hybrid multi-optimization of Least Square Support Vector Machine (LSSVM) and Bacterial Foraging Optimization Algorithm (BFOA) was designed in this study to produce accurate electricity price forecasts with optimized LSSVM parameters and input features. …”
    Article
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  15. 15

    Wireless sensor nodes deployment using multi-robot based on improved spanning tree algorithm by Arezoumand, Reza

    Published 2015
    “…One of the solutions to this problem is by using mobile robots with concern on exploration algorithm for mobile robot. …”
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    Thesis
  16. 16

    Discrete-time system identification using genetic algorithm with single parent-based mating technique by Zainuddin, Farah Ayiesya

    Published 2024
    “…This enhanced the GA's ability to avoid premature convergence and maintained a diverse solution set, leading to more optimal model selection. The study's results were validated using real-world data from industrial systems, including a hair dryer, an air compression system, and a flexible robot arm. …”
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    Thesis
  17. 17

    Information Theoretic-based Feature Selection for Machine Learning by Muhammad Aliyu, Sulaiman

    Published 2018
    “…Three major factors that determine the performance of a machine learning are the choice of a representative set of features, choosing a suitable machine learning algorithm and the right selection of the training parameters for a specified machine learning algorithm. …”
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    Thesis
  18. 18

    Image watermarking optimization algorithms in transform domains and feature regions by Tao, Hai

    Published 2012
    “…The achieved tradeoffs from these techniques between imperceptibility and robustness are controversial.To solve this problem,this study proposes the application of artificial intelligent techniques into digital watermarking by using discrete wavelet transform (DWT) and singular value decomposition (SVD).To protect the copyright information of digital images,the original image is decomposed according to two-dimensional discrete wavelet transform.Subsequently the preprocessed watermark with an affined scrambling transform is embedded into the vertical subband (HLm) coefficients in wavelet domain without compromising the quality of the image.The scaling factors are trained with the assistance of Particle Swarm Optimization (PSO).A new algorithmic framework is used to forecast feasibility of hypothesized watermarked images.In addition,the novelty is to associate the Hybrid Particle Swarm Optimization (HPSO),instead of a single optimization,as a model with SVD.To embed and extract the watermark,the singular values of the blocked host image are modified according to the watermark and scaling factors. …”
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    Thesis
  19. 19

    A Novel Hybrid Deep Learning Model Based on Simulated Annealing and Cuckoo Search Algorithms for Automatic Radiomics-Based COVID-19 Diagnosis by Saleh, Basma Jumaa, Omar, Zaid, As’ari, Muhammad Amir, Bhateja, Vikrant, Izhar, Lila Iznita

    Published 2025
    “…To further enhance COVID-19 lesion estimation, novel optimization strategies, including a hybrid simulated annealing-cuckoo search (SA-CS) algorithm, are introduced alongside the original SA method. …”
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    Article
  20. 20

    A krill herd behaviour inspired load balancing of tasks in cloud computing by Hasan, Raed Abdulkareem, Mohammed, Muamer N.

    Published 2017
    “…The speed, task cost, and weight of the tasks were first determined, after which, the Krill herd optimization algorithm was for the load balancing based on the measured parameters. …”
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