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  1. 1
    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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  2. 2
    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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  3. 3
    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
    “…Managing resources in grid computing system is complicated due to the distributed and heterogeneous nature of the resources.Stagnation in grid computing system may occur when all jobs require or are assigned to the same resources which lead to the resources having high workload or the time taken to process a job is high.This research proposes an Enhanced Ant Colony Optimization (EACO) algorithm that caters dynamic scheduling and load balancing in the grid computing system.The algorithm consists of three new mechanisms that organize the work of an ant colony i.e. initial pheromone value mechanism, resource selection mechanism and pheromone update mechanism.The resource allocation problem is modeled as a graph that can be used by the ant to deliver its pheromone.This graph consists of four types of vertices which are job, requirement, resource and capacity that are used in constructing the grid resource management element.The proposed EACO algorithm takes into consideration the capacity of resources and the characteristics of jobs in determining the best resource to process a job.EACO selects the resources based on the pheromone value on each resource which is recorded in a matrix form.The initial pheromone value of each resource for each job is calculated based on the estimated transmission time and execution time of a given job. …”
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  4. 4
    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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  5. 5
    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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    Final Year Project
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  6. 6
    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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  7. 7
    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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  8. 8
    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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  9. 9
    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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  10. 10
    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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  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 vehicle to grid planning and scheduling using double layer multi-objective algorithm

    Optimal vehicle to grid planning and scheduling using double layer multi-objective algorithm by Tan K.M., Ramachandaramurthy V.K., Yong J.Y.

    Published 2023
    “…Algorithms; Charging (batteries); Curve fitting; Electric load flow; Electric power systems; Electric vehicles; Energy management systems; Optimization; Reactive power; Real time control; Scheduling; Vehicles; Voltage control; Voltage regulators; Battery chargers; Bidirectional power flow; Multi objective algorithm; Optimization algorithms; Reactive power compensation; Real-time implementations; Revolutionary technology; Vehicle to grids; Electric power transmission networks; algorithm; electric vehicle; electricity supply; energy flow; energy planning; energy use; optimization; technological development…”
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  13. 13
    Optimal under voltage load shedding based on stability index by using artificial neural network

    Optimal under voltage load shedding based on stability index by using artificial neural network by Sharman, Sundarajoo

    Published 2020
    “…Nevertheless, to obtain the lowest amount to be shed in order to avoid voltage instability, optimization is required. An algorithm was developed to shed the optimal load by considering the load priority whereby the load with least priority will be shed first. …”
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  14. 14
    Optimization of load frequency control permancein two-area power system with PID controller using ICA and GSA algorithms / Mumuney Nurullahi Lekan

    Optimization of load frequency control permancein two-area power system with PID controller using ICA and GSA algorithms / Mumuney Nurullahi Lekan by Mumuney Nurullahi , Lekan

    Published 2018
    “…Hence, in this project, imperialist competitive algorithm (ICA) and gravitational search algorithm (GSA) are proposed in a LFC of two-area power system to optimize the performance of PID controllers using MATLAB and Simulink. …”
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  15. 15
    Optimal load shedding using bacteria foraging optimization for loss minimization / Siti Noorasyikin Ahmad Zaini

    Optimal load shedding using bacteria foraging optimization for loss minimization / Siti Noorasyikin Ahmad Zaini by Ahmad Zaini, Siti Noorasyikin

    Published 2007
    “…This thesis presented on optimal load shedding that had been used as the one of a tool to avoid the voltage instability. …”
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  16. 16
    Development of bacteria foraging optimization algorithm for cell formation in cellular manufacturing system considering cell load variations

    Development of bacteria foraging optimization algorithm for cell formation in cellular manufacturing system considering cell load variations by Nouri, Hossein, Tang, Sai Hong

    Published 2013
    “…The BFO algorithm is used to create machine cells and part families. …”
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  17. 17
    One day ahead daily peak hour load forecasting by using invasive weed optimization learning algorithm based Artificial Neural Network

    One day ahead daily peak hour load forecasting by using invasive weed optimization learning algorithm based Artificial Neural Network by Rahim, Muhammad Fitri

    Published 2012
    “…In this project, an Artificial Neural Network (ANN) trained by the Invasive Weed Optimization (IWO) learning algorithm is proposed for short term load forecasting (STLF) model. …”
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  18. 18
    Optimal loading analysis with penalty factors for generators using brute force method

    Optimal loading analysis with penalty factors for generators using brute force method by Alam, Mohammad Khurshed, Sulaiman, Mohd Herwan

    Published 2022
    “…This paper reports the optimal loading analysis method using the Brute Force method with and without considering the penalty factor of power line loss. …”
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  19. 19
    Optimal chiller loading solution for energy conservation using Barnacles Mating Optimizer algorithm

    Optimal chiller loading solution for energy conservation using Barnacles Mating Optimizer algorithm by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

    Published 2022
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  20. 20
    Optimization of neural network architecture using genetic algorithm for load forecasting

    Optimization of neural network architecture using genetic algorithm for load forecasting by Islam, B.U., Baharudin, Z., Raza, M.Q., Nallagownden, P.

    Published 2014
    “…The network structures are normally selected on the basis of the developer's prior knowledge or hit and trial approach is used for this purpose. ANN based models are frequently used for the prediction of future load, because of their learning and mapping ability to address the non linear nature of electrical load. …”
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