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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
    Firefly analytical hierarchy algorithm for optimal allocation and sizing of distributed generation in radial distribution network

    Firefly analytical hierarchy algorithm for optimal allocation and sizing of distributed generation in radial distribution network by Bujal, Noor Ropidah

    Published 2022
    “…The AHP was also found to yield accurate weights of the coefficient factors for each objective function compared to the weight-sum method generally used in studies. …”
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  5. 5
    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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  6. 6
    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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  7. 7
    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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  8. 8
    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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  9. 9
    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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  10. 10
    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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  11. 11
    A firefly algorithm based hybrid method for structural topology optimization

    A firefly algorithm based hybrid method for structural topology optimization by Gebremedhen, H.S., Woldemichael, D.E., Hashim, F.M.

    Published 2020
    “…The lower and upper limit of design variables (0 and 1) were used to find initial material distribution to initialize the firefly algorithm based section of the hybrid algorithm. …”
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  12. 12
    Multi-objective Binary Clonal Selection Algorithm In The Retrieval Phase Of Discrete Hopfield Neural Network With Weighted Systematic Satisfiability

    Multi-objective Binary Clonal Selection Algorithm In The Retrieval Phase Of Discrete Hopfield Neural Network With Weighted Systematic Satisfiability by Romli, Nurul Atiqah

    Published 2024
    “…Therefore, this thesis proposes a new systematic Satisfiability logical rule namely Weighted Systematic 2 Satisfiability that uses a weighted feature to control the distribution of the negative literals. …”
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  13. 13
    Selection of access network using cost function method in heterogeneous wireless network

    Selection of access network using cost function method in heterogeneous wireless network by Mohamad Tahir, Hatim, Al-Ghushami, Abdullah Hussein, Yahya, Zainor Ridzuan

    Published 2014
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  14. 14
    Enhanced Cuckoo Search Algorithm With Metaheuristic Components For Extracting The Maxima Of The Orientation Distribution Function

    Enhanced Cuckoo Search Algorithm With Metaheuristic Components For Extracting The Maxima Of The Orientation Distribution Function by Shehab, Mohammad Mohammad Said

    Published 2018
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  15. 15
    Levy slime mould algorithm for solving numerical and engineering optimization problems

    Levy slime mould algorithm for solving numerical and engineering optimization problems by J. J., Jui, M. A., Ahmad, M. I. M., Rashid

    Published 2022
    “…The proposed Levy Slime Mould Algorithm (LSMA) is a novel metaheuristic algorithm that integrates the Levy distribution into a new metaheuristic called Slime Mould Algorithm (SMA) for solving numerical and engineering problems. …”
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  16. 16
    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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  17. 17
    Robust Kernel Density Function Estimation

    Robust Kernel Density Function Estimation by Dadkhah, Kourosh

    Published 2010
    “…The proposed estimators are based on our newly developed Robust Kernel Weight Function (RKWF) and Robust Density Weight Function (RDWF). …”
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  18. 18
    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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  19. 19
    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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  20. 20
    Optimal multiple distributed generation output through rank evolutionary particle swarm optimization

    Optimal multiple distributed generation output through rank evolutionary particle swarm optimization by Jamian, J.J., Mustafa, M.W., Mokhlis, Hazlie

    Published 2015
    “…Moreover, the local best (P-best) and global best (G(best)) values are obtained in simplify manner in the REPSO algorithm. The performance of this new algorithm will be compared to 3 well-known PSO methods, which are Conventional Particle Swarm Optimization (CPSO), Inertia Weight Particle Swarm Optimization (IWPSO), and Iteration Particle Swarm Optimization (IPSO) on 10 mathematical benchmark functions, and solving the optimal DG output problem. …”
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