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  1. 1
    Performance evaluation of real-time multiprocessor scheduling algorithms

    Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

    Published 2016
    “…The CPU profiler of JavaTM VisualVM measures the number of invocations of scheduling event handlers (procedures) in each algorithm as well as the total time spent in all invocations of this handler. …”
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  2. 2
    Optimal placement of static VAR compensator using genetic algorithms

    Optimal placement of static VAR compensator using genetic algorithms by Mustafa, Mohd. Wazir, Wong, Yan Chiew

    Published 2008
    “…The developed algorithms have successfully obtained the best solution for optimal placement of SVC in the IEEE 9 buses system and TNB northern area 275kV 14-bus system…”
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  3. 3
    A Toolkit for Simulation of Desktop Grid Environment

    A Toolkit for Simulation of Desktop Grid Environment by FOROUSHAN, PAYAM CHINI

    Published 2014
    “…In this type of environment it is nearly impossible to prove the effectiveness of a scheduling algorithm. Hence the main objective of this study is to develop a desktop grid simulator toolkit for measuring and modeling scheduler algorithm performance. …”
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  4. 4
    Optimal design of three-phase static var compensation system

    Optimal design of three-phase static var compensation system by George M., Bakar M.B.B.A., Basu K.P.

    Published 2023
    “…This manuscript is aimed to emphasize the application of synchronous detection method (SDM) to develop and design three-phase static var compensation (SVC) systems with minimal complexity. …”
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  5. 5
    Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT

    Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT by Abdullah, Amran

    Published 2006
    “…Genetic Algorithm is one of the most popular optimization solutions used in various applications such as scheduling. …”
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  6. 6
    Improving Class Timetabling using Genetic Algorithm

    Improving Class Timetabling using Genetic Algorithm by Qutishat, Ahmed Mohammed Ali

    Published 2006
    “…This paper reports the power fill techniques using GA in scheduling. Class timetabling problem is one of the applications in scheduling. …”
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  7. 7
    Examination timetabling using genetic algorithm case study: KUiTTHO

    Examination timetabling using genetic algorithm case study: KUiTTHO by Mohd Salikon, Mohd Zaki

    Published 2005
    “…This paper reports the powerful techniques using GA in scheduling. Examination timetabling problem is one of the applications in scheduling. …”
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  8. 8
    Examination Timetabling Using Genetic Algorithm Case Study : KUiTTHO

    Examination Timetabling Using Genetic Algorithm Case Study : KUiTTHO by Mohd. Zaki, Mohd. Salikon

    Published 2005
    “…This paper reports the powerful techniques using GA in scheduling. Examination timetabling problem is one of the applications in scheduling. …”
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  9. 9
    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection

    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

    Published 2022
    “…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
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  10. 10
    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
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  11. 11
    Batch mode heuristic approaches for efficient task scheduling in grid computing system

    Batch mode heuristic approaches for efficient task scheduling in grid computing system by Maipan-Uku, Jamilu Yahaya

    Published 2016
    “…Many algorithms have been implemented to solve the grid scheduling problem. …”
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  12. 12
    Optimal operation and control of hybrid power systems with stochastic renewables and FACTS devices: An intelligent multi-objective optimization approach

    Optimal operation and control of hybrid power systems with stochastic renewables and FACTS devices: An intelligent multi-objective optimization approach by Premkumar M., Hashim T.J.T., Ravichandran S., Sin T.C., Chandran R., Alsoud A.R., Jangir P.

    Published 2025
    “…Employing both single- and multi-objective optimization algorithms, the research addresses the OPF problem in a modified IEEE-30 bus system through various case studies. …”
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  13. 13
    Multistage artificial immune system for static var compensator planning

    Multistage artificial immune system for static var compensator planning by Siti Chadijah Mohd Nasir

    Published 2024
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  14. 14
    Optimal Reactive Power Dispatch for Voltage Stability Improvement Considering Line Contingencies using PSO

    Optimal Reactive Power Dispatch for Voltage Stability Improvement Considering Line Contingencies using PSO by Nor Rul Hasma, Abdullah, I., Musirin

    Published 2013
    “…The proposed algorithm gives an optimal setting of control devices such as switchable VAR compensator and able to minimize total transmission losses, improved voltage stability and increase voltage profile of the system. …”
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  15. 15
    The study of ant colony optimization (ACO) parameters for STATCOM optimization / Melor Md Hodari

    The study of ant colony optimization (ACO) parameters for STATCOM optimization / Melor Md Hodari by Md Hodari, Melor

    Published 2010
    “…The proposed technique was tested using the standard IEEE 30-bus system and the capability of developed ACO in solving continuous optimization problems has been revealed as the added value in the algorithm.…”
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  16. 16
    The study of ant colony optimization (ACO) parameters for STATCOM optimization: article / Melor Md Hodari

    The study of ant colony optimization (ACO) parameters for STATCOM optimization: article / Melor Md Hodari by Md Hodari, Melor

    Published 2010
    “…The proposed technique was tested using the standard IEEE 30-bus system and the capability of developed ACO in solving continuous optimization problems has been revealed as the added value in the algorithm.…”
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  17. 17
    Classroom finder system with student availability, space and time constraint

    Classroom finder system with student availability, space and time constraint by Loh, Yong Bin

    Published 2024
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  18. 18
    Optimization of support vector machine parameters in modeling of Iju deposit mineralization and alteration zones using particle swarm optimization algorithm and grid search method

    Optimization of support vector machine parameters in modeling of Iju deposit mineralization and alteration zones using particle swarm optimization algorithm and grid search method by Abbaszadeh M., Soltani-Mohammadi S., Ahmed A.N.

    Published 2023
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  19. 19
    Evaluating Adan vs. Adam: an analysis of optimizer performance in deep learning

    Evaluating Adan vs. Adam: an analysis of optimizer performance in deep learning by Ismail, Amelia Ritahani, Azhary, Muhammad Zulhazmi Rafiqi, Hitam, Nor Azizah

    Published 2025
    “…Choosing a suitable optimization algorithm in deep learning is essential for effective model development as it significantly influences convergence speed, model performance, and the success of the train- ing process. …”
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  20. 20
    Smart student timetable planner

    Smart student timetable planner by Wong, Xin Tong

    Published 2025
    “…Course data is managed in CSV format, parsed into JSON for fast processing, while sessionStorage and localStorage handle user data within active sessions. 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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