Search Results - (( course optimization method algorithm ) OR ( simulation optimization method algorithm ))

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  1. 1

    Using Electromagnetism-like algorithm and genetic algorithm to optimize time of task scheduling for dual manipulators by Abed I.A., Sahari K.S.M., Koh S.P., Tiong S.K., Jagadeesh P.

    Published 2023
    “…A method based on Electromagnetism-Like algorithm (EM) and Genetic Algorithm (GA) is proposed to determine the time-optimal task scheduling for dual robot manipulators. …”
    Conference paper
  2. 2

    Evaluate the performance of university timetabling problem with various artificial intelligence techniques by Hooi, Charmaine Wai Yee

    Published 2025
    “…Over time, numerous algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Simulated Annealing (SA), and other approaches have been introduced to address the challenges of optimizing class schedules. …”
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    Final Year Project / Dissertation / Thesis
  3. 3

    Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions by Abbas, Iraq Tareq

    Published 2018
    “…In this thesis, in order to solve single objective optimization problem and bi-objective objective optimization problem in non-linear functions, two methods are created during the course of the present work. …”
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    Thesis
  4. 4

    Investigating a round robin strategy over multi algorithms in optimising the quality of university course timetables by Abdullah S., Shaker K., Shaker H.

    Published 2023
    “…In this study, we apply three algorithms, that is, Great Deluge, Simulated Annealing and Hill Climbing where the Round Robin algorithm is used as control strategy in choosing the algorithm to be employed at the current stage. …”
    Article
  5. 5

    Optimization of the Time of Task Scheduling for Dual Manipulators using a Modified Electromagnetism-Like Algorithm and Genetic Algorithm by Abed I.A., Koh S.P., Sahari K.S.M., Jagadeesh P., Tiong S.K.

    Published 2023
    “…A method based on a modified electromagnetism-like with two-direction local search algorithm (MEMTDLS) and genetic algorithm (GA) is proposed to determine the optimal time of task scheduling for dual-robot manipulators. …”
    Article
  6. 6

    Hybridizing harmony search with local search based metaheuristic for solving curriculum based university course timetabling / Juliana Wahid by Wahid, Juliana

    Published 2017
    “…Thus, this thesis proposed hybrid algorithms between HSA and local search based methods (simulated annealing (SA) and/or great deluge (GD)) to enhance the HSA performance for solving curriculum-based course timetabling (CBCTT) problem which is the variant of UCTP. …”
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    Thesis
  7. 7

    Hybridizing harmony search with local search based metaheuristic for solving curriculum based university course timetabling / Juliana Wahid by Wahid, Juliana

    Published 2017
    “…Thus, this thesis proposed hybrid algorithms between HSA and local search based methods (simulated annealing (SA) and/or great deluge (GD)) to enhance the HSA performance for solving curriculum-based course timetabling (CBCTT) problem which is the variant of UCTP. …”
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    Book Section
  8. 8

    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
  9. 9

    Solving an application of university course timetabling problem by using genetic algorithm by Norhana, Shaibatul Khadri

    Published 2022
    “…Therefore, this study produces the best timetable using GA to solve clashed courses, optimize room utilization and maximize lecturers’ preferences. …”
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    Thesis
  10. 10

    Hybrid meta-heuristic algorithm for solving multi-objective aggregate production planning in fuzzy environment by Kalaf, Kalaf, Bayda Atiya

    Published 2017
    “…During the course of the present work, two fuzzy methods (modified Zimmermanns approach and modified angelovs approach ) and fourmeta-heuristics and hybrid meta heuristics including; simulated annealing (SA), modified simulated annealing (MSA), hybrid modified simulated annealing and simplex downhill (MSASD), hybrid modified simulated annealing and modified particle swarm optimization (MSAPSO) were proposed. …”
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    Thesis
  11. 11

    A basic study on hybrid systems for small race car to improve dynamic performance using lap time simulation by Kobayashi, Ikkei, Ogawa, Kazuki, Uchino, Daigo, Ikeda, Keigo, Kato, Taro, Endo, Ayato, Mohamad Heerwan, Peeie, Narita, Takayoshi, Kato, Hideaki

    “…To apply these controls to race cars, which are required to be fast, it is necessary to obtain the reference input, which is the optimal velocity and yaw angle while traveling the course of the servo system, and simulations of the competition track must be carried out. …”
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    Article
  12. 12

    Deep reinforcement learning based resource allocation strategy in cloud-edge computing system by Ahmed Adhoni, Zameer, Habelalmateen, Mohammed, DR Janardhana, DR Janardhana, Abdul Sattar, Khalid Nazim, Audah, Lukman

    Published 2024
    “…In this work, the research focus on the simulation testing of the MAL-DRL algorithm against classical Random Allocation (RA) and singe agent DRL methods. …”
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    Conference or Workshop Item
  13. 13

    Deep reinforcement learning based resource allocation strategy in cloud-edge computing system by Ahmed Adhoni, Zameer, Habelalmateen, Mohammed I, D R, Janardhana, Abdul Sattar, Khalid Nazim, Audah, Lukman

    Published 2024
    “…In this work, the research focus on the simulation testing of the MAL-DRL algorithm against classical Random Allocation (RA) and singe agent DRL methods. …”
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    Conference or Workshop Item
  14. 14

    Intelligent traffic lights using Q-learning by Mohd Yusop, Muhammad Aminuddin, Mansor, Hasmah, Gunawan, Teddy Surya, Nasir, Haidawati,

    Published 2022
    “…Q-learning derives benefits from past experiences and determines the optimal course of action based on them. The performance of the proposed system has been measured against that of the traditional system, which is a fixed time cycle system. …”
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    Proceeding Paper
  15. 15

    A harmony search algorithm for university course timetabli by Al-Betar, Mohammed Azmi, Khader, Ahamad Tajudin

    Published 2012
    “…The major thrust of this algorithm lies in its ability to integrate the key components of population-based methods and local search-based methods in a simple optimization model. …”
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    Article
  16. 16

    Optimization of turning parameters using genetic algorithm method by Shah Izwandi, Mohd Zawawi

    Published 2008
    “…The simulation based on Genetic Algorithm are successful develop and the optimum parameters values are obtained from the simulation.…”
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    Undergraduates Project Papers
  17. 17

    Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation by Khan, Abdullah

    Published 2022
    “…This thesis proposes and simulates the three novel optimization algorithms to handle DG allocation, different single-objective, and multi-objective OPF problems. …”
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    Thesis
  18. 18

    A discrete simulated kalman filter optimizer for combinatorial optimization problems by Suhazri Amrin, Rahmad

    Published 2022
    “…An example of a numerical algorithm is the simulated Kalman filter (SKF). Various method has been introduced as an extension of a numerical algorithm to adapt it to a discrete search space. …”
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    Thesis
  19. 19

    Route optimization using shortest path method / Muhamad Faisal Amin Shakri by Shakri, Muhamad Faisal Amin

    Published 2025
    “…Therefore, the effectiveness of route planning is very essential. The method to study route optimization is called shortest path method. …”
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    Thesis
  20. 20

    Improved particle swarm optimization by fast annealing algorithm by Bashath, Samar, Ismail, Amelia Ritahani

    Published 2019
    “…We also apply the algorithm in clustering problem, and the results shows that the proposed method has better accuracy than the optimization methods.…”
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    Proceeding Paper