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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
    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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  3. 3
    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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  4. 4
    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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  5. 5
    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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  6. 6
    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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  7. 7
    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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  8. 8
    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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  9. 9
    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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  10. 10
    PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM

    PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM by ABDALLA, OSMAN AHMED

    Published 2011
    “…Particularly, GA is utilized to determine the optimal number of hidden layers, number of neurons in each hidden layer, type of training algorithm, type of activation function of hidden and output neurons, initial weight, learning rate, momentum term, and epoch size of a multilayer feed-forward ANN. …”
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  11. 11
    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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  12. 12
    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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  13. 13
    Investigating feed mix problem approaches: An overview and potential solution

    Investigating feed mix problem approaches: An overview and potential solution by Abd Rahman, Rosshairy, Chooi, Leng Ang, Ramli, Razamin

    Published 2010
    “…Hybrid GA technique with artificial bee algorithm is expected to reduce the penalty function and provide a better solution for the feed mix problem.…”
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  14. 14
    Smart appointment organizer for mobile application / Mohd Syafiq Adam

    Smart appointment organizer for mobile application / Mohd Syafiq Adam by Adam, Mohd Syafiq

    Published 2009
    “…In creating this application, NetBeans IDE 6.5and Java Micro Edition (Java ME) are used. …”
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  15. 15
    Grouper fish feed formulation using enhanced evolutionary algorithm with fibonacci rabbit initialization and binary-standard deviation tournament selection

    Grouper fish feed formulation using enhanced evolutionary algorithm with fibonacci rabbit initialization and binary-standard deviation tournament selection by Soong, Cai Juan

    Published 2023
    “…The main contribution of this research is the development of feed formulation using Evolutionary Algorithm (EA) with four variations of EA, which are Semi-Random Initialization – Binary Tournament Selection - EA (SR-BT-EA), Fibonacci Rabbit Initialization – Binary Tournament Selection - EA (FR-BT-EA), Semi-Random Initialization - Binary- Standard Deviation Tournament Selection - EA (SR-SD-EA) and Fibonacci Rabbit Initialization - Binary-Standard Deviation Tournament Selection - EA (FR-SD-EA). …”
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  16. 16
    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
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  17. 17
    Development of generalized feed forward network for predicting annual flood (depth) of a tropical river

    Development of generalized feed forward network for predicting annual flood (depth) of a tropical river by Salarpour, Mohsen, Zulkifli Yusop, Jajarmizadeh, Milad, Fadhilah Yusof

    Published 2014
    “…This study aimed at developing a Generalized Feed Forward (GFF) network model for predicting annual flood (depth) of Johor River in Peninsular Malaysia. …”
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  18. 18
    A multi-criteria proximal bundle-based optimization approach to chick-mash feed formulation

    A multi-criteria proximal bundle-based optimization approach to chick-mash feed formulation by Abayomi, Olalere Olusegun, Ruth, Alara Oluwaseun, Bala, Mohamed Saad, Twibi, Mohamed Farag

    Published 2016
    “…The algorithm of this method is based on the objective functions classification. …”
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  19. 19
    Cash-flow analysis of a wind turbine operator

    Cash-flow analysis of a wind turbine operator by Muhamad Razali N.M., Hashim A.H.

    Published 2023
    “…The paper outlines a method to evaluate the distribution of WTG operator's daily cash-flow by developing an algorithm based on Monte-Carlo technique. …”
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  20. 20
    Development Of Generative Computer-Aided Process Planning System For Lathe Machining

    Development Of Generative Computer-Aided Process Planning System For Lathe Machining by Zubair, Ahmad Faiz

    Published 2019
    “…Furthermore, to minimize unit production cost, machining parameters including cutting speed (CS), feed rate (f) and depth of cut (d) were optimized for regular form surfaces by using firefly algorithm (FA). …”
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