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  1. 1
    Ant colony optimization algorithm for load balancing in grid computing

    Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2012
    “…This research proposes an enhancement of the ant colony optimization algorithm that caters for dynamic scheduling and load balancing in the grid computing system. …”
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    Monograph
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  2. 2
    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing

    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

    Published 2011
    “…This research proposes an Enhanced Ant Colony Optimization (EACO) algorithm that caters dynamic scheduling and load balancing in the grid computing system. …”
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  3. 3
    A Micro-Genetic Algorithm Approach for Soft Constraint Satisfaction Problem in University Course Scheduling

    A Micro-Genetic Algorithm Approach for Soft Constraint Satisfaction Problem in University Course Scheduling by Abd. Halim, Bohadean @ Bohari

    Published 2013
    “…A university course timetabling problem is a combination of optimization problems. …”
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  4. 4
    Meta-Heuristic Algorithms for Learning Path Recommender at MOOC

    Meta-Heuristic Algorithms for Learning Path Recommender at MOOC by Son, N.T., Jaafar, J., Aziz, I.A., Anh, B.N.

    Published 2021
    “…The recommended studying path satisfies several learner criteria, such as the critical learning path, number of enrollments, learning duration, popularity, rating of previous learners, and cost. We have developed Metaheuristic algorithms includes the Genetic Algorithm (GA) and Ant Colony Optimization Algorithm (ACO), to solve the proposed model. …”
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  5. 5
    Evaluate the performance of university timetabling problem with various artificial intelligence techniques

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

    Published 2025
    “…The project focuses on developing an automated university course timetable scheduling tool using Genetic Algorithm (GA). …”
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  6. 6
    Web based personalized university timetable for UiTM students using genetic algorithm / Mohd Radhi Fauzan Jamli and Ahmad Firdaus Ahmad Fadzil

    Web based personalized university timetable for UiTM students using genetic algorithm / Mohd Radhi Fauzan Jamli and Ahmad Firdaus Ahmad Fadzil by Jamli, Mohd Radhi Fauzan, Ahmad Fadzil, Ahmad Firdaus

    Published 2024
    “…The research endeavors to develop a web-based system specifically designed to create personalized university timetables for Universiti Teknologi MARA (UiTM) students using genetic algorithms, aiming to address the urgent need for a customizable timetable solution catering to the diverse scheduling requirements of both repeater and non-repeater students while optimizing course group selection to minimize conflicts and enhance scheduling flexibility. …”
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  7. 7
    Resource management in grid computing using ant colony optimization

    Resource management in grid computing using ant colony optimization by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2011
    “…Resources with high pheromone value are selected to process the submitted jobs.Global pheromone update is performed after completion processing the jobs in order to reduce the pheromone value of resources.A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against other ant based algorithm, in terms of resource utilization.Experimental results show that EACO produced better grid resource management solution.…”
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  8. 8
    Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter

    Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter by Azhar, Nur Huwaina

    Published 2019
    “…Cloudsim is used as Discrete Event Simulation tool and Java as coding language to evaluate LACE algorithm. …”
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  9. 9
    Solving an application of university course timetabling problem by using genetic algorithm

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

    Published 2022
    “…The system can help SQS or any other academic schools or institutions to easily develop course timetabling in the coming semesters.…”
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  10. 10
    Using Electromagnetism-like algorithm and genetic algorithm to optimize time of task scheduling for dual manipulators

    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. …”
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  11. 11
    Exam hall allocation using genetic algorithm / Norisyani Binti Fauzai

    Exam hall allocation using genetic algorithm / Norisyani Binti Fauzai by Fauzai, Norisyani

    Published 2021
    “…In this project an automated exam hall allocation prototype was developed using the genetic algorithm since this algorithm is commonly used to produce high-quality optimization solutions. …”
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  12. 12
    An efficient IDS using hybrid Magnetic swarm optimization in WANETs

    An efficient IDS using hybrid Magnetic swarm optimization in WANETs by Sadiq, Ali Safa, Alkazemi, Basem Y., Mirjalili, Seyedali, Noraziah, Ahmad, Khan, Suleman, Ihsan, Ali, Pathan, Al-Sakib Khan, Ghafoor, Kayhan Zrar

    Published 2018
    “…In order to improve the accuracy of artificial neural network (ANN) classifier, we have integrated our proposed hybrid magnetic optimization algorithm-particle swarm optimization (MOA-PSO) technique. …”
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  13. 13
    An Efficient IDS Using Hybrid Magnetic Swarm Optimization in WANETs

    An Efficient IDS Using Hybrid Magnetic Swarm Optimization in WANETs by Sadiq, Ali Safaa, Alkazemi, Basem, Mirjalili, Seyedali, Ahmed, Noraziah, Khan, Suleman, Ali, Ihsan, Pathan, Al-Sakib Khan, Ghafoor, Kayhan Zrar

    Published 2018
    “…In order to improve the accuracy of artificial neural network (ANN) classifier, we have integrated our proposed hybrid magnetic optimization algorithm-particle swarm optimization (MOA-PSO) technique. …”
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  14. 14
    Optimization of the Time of Task Scheduling for Dual Manipulators using a Modified Electromagnetism-Like Algorithm and Genetic Algorithm

    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. …”
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  15. 15
    CSC649 - Special Topics in Computer Science / College of Computing, Informatics and Media

    CSC649 - Special Topics in Computer Science / College of Computing, Informatics and Media by UiTM, College of Computing, Informatics and Media

    Published 2022
    “…The course will cover specialized technology and described in terms of frameworks and problem formulations, standard models, methods, computational tools, algorithms, as well as methodologies to evaluate the system and select optimal models. …”
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  16. 16
    CSC649: Special Topics in Computer Science / College of Computing, Informatics and Mathematics

    CSC649: Special Topics in Computer Science / College of Computing, Informatics and Mathematics by UiTM, College of Computing, Informatics and Mathematics

    Published 2018
    “…The course will cover specialized technology and described in terms of frameworks and problem formulations, standard models, methods, computational tools, algorithms, as well as methodologies to evaluate the system and select optimal models. …”
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  17. 17
    Handbook of Machine Learning for Computational Optimization: Applications and Case Studies

    Handbook of Machine Learning for Computational Optimization: Applications and Case Studies by Jain, V., Juneja, S., Juneja, A., Kannan, R.

    Published 2021
    “…This handbook will provide readers with a leading edge to improving their products and processes through optimal and smarter machine learning techniques. This handbook focuses on new machine learning developments that can lead to newly developed applications. …”
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  18. 18
    Smart student timetable planner

    Smart student timetable planner by Wong, Xin Tong

    Published 2025
    “…A Genetic Algorithm forms the core scheduling engine, generating optimized timetables that respect both hard constraints, such as avoiding clashes, and soft constraints, such as personal preferences.The final output of this project is a functional web-based timetable planner that successfully enhances scheduling efficiency, reduces the likelihood of errors, and improves the overall academic planning experience. …”
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  19. 19
    Malaysian menu planning model using Self-adaptive Hybrid Genetic Algorithm (SHGA)

    Malaysian menu planning model using Self-adaptive Hybrid Genetic Algorithm (SHGA) by Mohd Razali, Siti Noor Asyikin, Engku Abu Bakar, Engku Muhammad Nazri, Ku-Mahamud, Ku Ruhana, Arbin, Norazman, Rusiman, Mohd Saifullah

    Published 2018
    “…We developed Malaysian menu planning model with the objectives to optimize the budget allocation for each student, maximize the variety of daily meals, maximize the caterer’s ability, accomplish meals course structures and fulfill the standard recommended nutrient intake (RNI). …”
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  20. 20
    Malaysian menu planning model using Self-Adaptive Hybrid Genetic Algorithm (SHGA)

    Malaysian menu planning model using Self-Adaptive Hybrid Genetic Algorithm (SHGA) by Mohd Razali, Siti Noor Asyikin, Engku Abu Bakar, Engku Muhammad Nazri, Ku Mahamud, Ku Ruhana, Arbin, Norazman, Rusiman, Mohd Saifullah

    Published 2018
    “…We developed Malaysian menu planning model with the objectives to optimize the budget allocation for each student, maximize the variety of daily meals, maximize the caterer’s ability, accomplish meals course structures and fulfill the standard recommended nutrient intake (RNI). …”
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