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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
    “…The resource allocation problem is modeled as a graph that can be used by the ant to deliver its pheromone. …”
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    Thesis
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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
    “…The resource allocation problem is modelled 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. …”
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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
    “…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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    Monograph
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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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    Conference or Workshop Item
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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
    Solving the minimum dominating set problem of partitioned graphs using a hybrid bat algorithm

    Solving the minimum dominating set problem of partitioned graphs using a hybrid bat algorithm by Abed, S.A., Rais, H.M.

    Published 2020
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  7. 7
    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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  8. 8
    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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  9. 9
    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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  10. 10
    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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  11. 11
    VISUALIZATION OF GENETIC ALGORITHM BASED ON 2-D GRAPH TO ACCELERATE THE SEARCHING WITH HUMAN INTERVENTIONS.

    VISUALIZATION OF GENETIC ALGORITHM BASED ON 2-D GRAPH TO ACCELERATE THE SEARCHING WITH HUMAN INTERVENTIONS. by FAROOQ, HUMERA

    Published 2012
    “…A tool termed as VIGA-20 (Visualization of Genetic Algorithm using 2-0 Graph) is implemented to accomplish this goal. …”
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  12. 12
    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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  13. 13
    Multiregion segmentation of mammogram images by using parametric kernel graph cut algorithm / Nurhanani Abdul Rahim, Nor Farah Nabilah Mushtafa and Nadhirah Afiqah Zailan

    Multiregion segmentation of mammogram images by using parametric kernel graph cut algorithm / Nurhanani Abdul Rahim, Nor Farah Nabilah Mushtafa and Nadhirah Afiqah Zailan by Abdul Rahim, Nurhanani, Mushtaf, Nor Farah Nabilah, Zailan, Nadhirah Afiqah

    Published 2019
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    Student Project
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  14. 14
    Optimizing boarding school schedule using graph coloring: case study of Sekolah Menengah Sultan Abdul Halim / Nur Farhana Mohd Asri

    Optimizing boarding school schedule using graph coloring: case study of Sekolah Menengah Sultan Abdul Halim / Nur Farhana Mohd Asri by Mohd Asri, Nur Farhana

    Published 2022
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    Research Reports
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  15. 15
    Performance analyses of graph heuristics and selected trajectory metaheuristics on examination timetable problem

    Performance analyses of graph heuristics and selected trajectory metaheuristics on examination timetable problem by Mandal, Ashis Kumar, M. N. M., Kahar

    Published 2020
    “…For constructing the feasible solution, six graph heuristics are used. They are largest degree (LD), largest weighted degree (LWD), largest enrolment degree (LE), and three hybrid heuristic with saturation degree (SD) such as SD-LD, SD-LE, and SD-LWD. …”
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  16. 16
    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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  17. 17
    Performance analysis of graph heuristics and selected trajectory metaheuristics on examination timetable problem

    Performance analysis of graph heuristics and selected trajectory metaheuristics on examination timetable problem by Mandal, Ashis Kumar, Mohd Nizam Mohmad, Kahar

    Published 2020
    “…For constructing the feasible solution, six graph heuristics are used. They are largest degree (LD), largest weighted degree (LWD), largest enrolment degree (LE), and three hybrid heuristics with saturation degree (SD) such as SD-LD, SD-LE, and SD-LWD. …”
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  18. 18
    Enhancement of Ant System Algorithm for Course Timetabling Problem

    Enhancement of Ant System Algorithm for Course Timetabling Problem by Djamarus, Djasli

    Published 2009
    “…Results of the experiments that were conducted using various data sets showed that the proposed algorithm produced better course schedule solution than the Greedy Algorithm, Genetic Algorithm, and other variants of Ant System Algorithm.…”
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  19. 19
    Hybrid bat algorithm for minimum dominating set problem

    Hybrid bat algorithm for minimum dominating set problem by Abed, S.A., Rais, H.M.

    Published 2017
    “…However, population-based algorithms are not good in exploiting the search space in comparison to single-solution based methods, therefore we included simulated annealing (SA) algorithm to balance between exploitation and exploration in order to reach a best possible solution. …”
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  20. 20
    Construction of initial solution population for curriculum-based course timetabling using combination of graph heuristics

    Construction of initial solution population for curriculum-based course timetabling using combination of graph heuristics by Wahid, Juliana, Mohd Hussin, Naimah

    Published 2016
    “…The construction of population of initial solution is a crucial task in population-based metaheuristic approach for solving curriculum-based university course timetabling problem because it can affect the convergence speed and also the quality of the final solution.This paper presents an exploration on combination of graph heuristics in construction approach in curriculum based course timetabling problem to produce a population of initial solutions.The graph heuristics were set as single and combination of two heuristics.In addition, several ways of assigning courses into room and timeslot are implemented.All settings of heuristics are then tested on the same curriculum based course timetabling problem instances and are compared with each other in terms of number of population produced.The result shows that combination of largest degree followed by saturation degree heuristic produce the highest number of population of initial solutions.The results from this study can be used in the improvement phase of algorithm that uses population of initial solutions…”
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