Search Results - (( simulation optimization task algorithm ) OR ( using functional based algorithm ))

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  1. 1

    A harmony search-based learning algorithm for epileptic seizure prediction by Kee, Huong Lai, Zainuddin, Zarita, Ong, Pauline

    Published 2016
    “…The proposed harmony search-based learning algorithm is used in the task of epileptic seizure prediction. …”
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    Article
  2. 2

    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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    Thesis
  3. 3

    A discrete event simulation framework for utility accrual scheduling algorithm in uniprocessor environment by Ahmad, Idawaty, K. Subramaniam, Shamala, Othman, Mohamed, Ahmad Zukarnain, Zuriati

    Published 2011
    “…GUS is one of the existing TUF/UA scheduling algorithms that consider the Time/Utility Function (TUF) of the executed tasks in its scheduling decision. …”
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    Article
  4. 4

    Dynamic obstacle handling in multi-robot coverage by Tay, Wing Le

    Published 2024
    “…The impacts of the modified algorithm’s parameters on simulation results were also studied to determine the optimal parameters for achieving better performance. …”
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    Final Year Project / Dissertation / Thesis
  5. 5

    Space allocation for examination scheduling using Genetic Algorithm / Alya Kauthar Azman by Azman, Alya Kauthar

    Published 2025
    “…This study applies Genetic Algorithms (GA) to optimize space distribution for test scheduling, addressing the challenge of managing multiple test sessions across distinct locations. …”
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    Thesis
  6. 6

    Solving large-scale problems using multi-swarm particle swarm approach by Salih, Sinan Q., Alsewari, Abdulrahman A.

    Published 2018
    “…The proposed approach strived to scale up the application of the (PSO) algorithm towards solving large-scale optimization tasks of up to 1000 real-valued variables. …”
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    Article
  7. 7

    HSO: A hybrid swarm optimization algorithm for reducing energy consumption in the cloudlets by Hasan, Raed Abdulkareem, Mostafa, A. Mohammed, Salih, Zeyad Hussein, M. A., Ameedeen, Tapus, Nicolae, Mohammed, Muamer N.

    Published 2018
    “…With the proposed model, the performance of the Hybrid swarm algorithm was significantly increased, as observed by optimizing the number of tasks through simulation, (power consumption was reduced by 42%). …”
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    Article
  8. 8

    Fair bandwidth distribution marking and scheduling algorithm in network traffic classification by Al-Kharasani, Ameen Mohammed Abdulkarem

    Published 2019
    “…Finally, propose a new method of obtaining optimal parameters dropping functions for Random Early Detection (RED) algorithm. …”
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    Thesis
  9. 9

    An adaptively switching iteration strategy for population based metaheuristics / Nor Azlina Ab. Aziz by Nor Azlina, Ab. Aziz

    Published 2017
    “…Experiments conducted using three parent algorithms namely particle swarm optimization (PSO), which is a popular population-based optimizer with population and individual memories, gravitational search algorithm (GSA), a memoryless young optimizer, and simulated Kalman filter (SKF), a newly introduced optimization algorithm that use population’s memory to guide an agent’s search, show that iteration strategy is an algorithm dependent parameter as well as function dependent. …”
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    Thesis
  10. 10

    Transmission loss minimization using SVC based on particle swarm optimization by Jumaat, S.A., Musirin, I., Othman, M.M., Mokhlis, Hazlie

    Published 2011
    “…Validation through the implementation on the IEEE 26-bus system shows that the PSO is found feasible to achieve the task. The simulations results are compared with those obtained from the Bee Algorithm (BA) technique in the attempt to highlight its merit.…”
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    Conference or Workshop Item
  11. 11

    Optimal location and sizing of SVC using Particle Swarm Optimization technique by Jumaat, S.A., Musirin, I., Othman, M.M., Mokhlis, Hazlie

    Published 2011
    “…Particle Swarm Optimization (PSO) is population-based stochastic search algorithms approaches as the potential techniques to solving such a problem. …”
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    Conference or Workshop Item
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    A memory-guided Jaya algorithm to solve multi-objective optimal power flow integrating renewable energy sources by Ahmadipour M., Ali Z., Ramachandaramurthy V.K., Ridha H.M.

    Published 2025
    “…A smart memory-based strategy is incorporated into the algorithm to enhance solution optimality, convergence properties, and exploitation capabilities. …”
    Review
  15. 15

    Optimised multi-robot path planning via smooth trajectory generation by Loke, Zhi Yu

    Published 2024
    “…A MPSO algorithm, without path smoothening, is used for comparison. …”
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    Final Year Project / Dissertation / Thesis
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    Removal of BCG artefact from concurrent fMRI-EEG recordings based on EMD and PCA by Javed, E., Faye, I., Malik, A.S., Abdullah, J.M.

    Published 2017
    “…Results The method was tested with both simulated and real EEG data of 11 participants. From the simulated data, the similarity index between the extracted BCG and the simulated BCG showed the effectiveness of the proposed method in BCG removal. …”
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    Article
  19. 19

    Development of optimized maintenance scheduling model for coal-fired power plant boiler by Noor Fazreen Binti Ahmad Fuzi, Ms.

    Published 2023
    “…The MILP model was shown to be a useful decision-making tool for optimizing maintenance scheduling under different circumstances when tested with PSO and some trial simulations. …”
    text::Thesis
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    Task scheduling in cloud computing environment using hybrid genetic algorithm and bat algorithm by Muhammad Syahril Mohamad Sainal

    Published 2022
    “…Meta-heuristic algorithms are mostly used to solve this problem. For example, Genetic Algorithm with Particle Swarm Optimization, Genetic Algorithm with Artificial Bee Colony Algorithms (ABC) and Genetic Algorithm with Ant Colony Optimization Algorithms. …”
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    Academic Exercise