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  1. 1
    Multi objective bee colony optimization framework for grid job scheduling

    Multi objective bee colony optimization framework for grid job scheduling by Alyaseri, Sana, Ku-Mahamud, Ku Ruhana

    Published 2013
    “…Grid computing is the infrastructure that involves a large number of resources like computers, networks and databases which are owned by many organizations.Job scheduling problem is one of the key issues because of high heterogeneous and dynamic nature of resources and applications in the grid computing environment.Bee colony approach has been used to solve this problem because it can be easily adapted to the grid scheduling environment.The bee algorithms have shown encouraging results in terms of time and co st.In this paper a framework for multi objective bee colony optimization is proposed to schedule batch jobs to available resources where the number of jobs is greater than the number of resources.Pareto analysis and k-means analysis are integrated in the bee colony optimization algorithm to facilitate the scheduling of jobs to resources.…”
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  2. 2
    Optimisation of energy efficient hybrid flowshop scheduling problem using firefly algorithm

    Optimisation of energy efficient hybrid flowshop scheduling problem using firefly algorithm by M. F. F., Ab Rashid, Mohd Abdul, Hadi Osman

    Published 2020
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  3. 3
    Independent And Dependent Job Scheduling Algorithms Based On Weighting Model For Grid Environment

    Independent And Dependent Job Scheduling Algorithms Based On Weighting Model For Grid Environment by M. Al-Najjar, Hazem

    Published 2018
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  4. 4
    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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  5. 5
    A static jobs scheduling for independent jobs in Grid Environment by using Fuzzy C-Mean and Genetic algorithms

    A static jobs scheduling for independent jobs in Grid Environment by using Fuzzy C-Mean and Genetic algorithms by Lorpunmanee, Siriluck, Md. Sap, Mohd. Noor, Abdullah, Abdul Hanan, Srinoy, Surat

    Published 2006
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  6. 6
    Fuzzy C-Mean And Genetic Algorithms Based Scheduling For Independent Jobs In Computational Grid

    Fuzzy C-Mean And Genetic Algorithms Based Scheduling For Independent Jobs In Computational Grid by Lorpunmanee, Siriluck, Md Sap, Mohd Noor, Abdullah, Abdul Hanan

    Published 2006
    “…Our model presents the method of the jobs classifications based mainly on Fuzzy C-Mean algorithm and mapping the jobs to the appropriate resources based mainly on Genetic algorithm. …”
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  7. 7
    Job online scheduling within dynamic grid environment

    Job online scheduling within dynamic grid environment by Lorpunmanee, Siriluck, Md. Sap, Mohd. Noor, Abdullah, Abdul Hanan

    Published 2008
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  8. 8
    Scheduling jobs in computational grid using hybrid ACS and GA approach

    Scheduling jobs in computational grid using hybrid ACS and GA approach by Alobaedy, Mustafa Muwafak, Ku-Mahamud, Ku Ruhana

    Published 2014
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  9. 9
    Ant colony optimization algorithm for dynamic scheduling of jobs in computational grid

    Ant colony optimization algorithm for dynamic scheduling of jobs in computational grid by Ku-Mahamud, Ku Ruhana, Ramli, Razamin, Yusof, Yuhanis, Mohamed Din, Aniza, Mahmuddin, Massudi

    Published 2012
    “…Job scheduling problem is classified as an NP-hard problem.Such a problem can be solved only by using approximate algorithms such as heuristic and meta-heuristic algorithms.Among different optimization algorithms for job scheduling, ant colony system algorithm is a popular meta-heuristic algorithm which has the ability to solve different types of NP-hard problems.However, ant colony system algorithm has a deficiency in its heuristic function which affects the algorithm behavior in terms of finding the shortest connection between edges.This research focuses on a new heuristic function where information about recent ants’ discoveries has been considered.The new heuristic function has been integrated into the classical ant colony system algorithm.Furthermore, the enhanced algorithm has been implemented to solve the travelling salesman problem as well as in scheduling of jobs in computational grid.A simulator with dynamic environment feature to mimic real life application has been development to validate the proposed enhanced ant colony system algorithm. …”
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  10. 10
    Ant colony algorithm for job scheduling in grid computing

    Ant colony algorithm for job scheduling in grid computing by Ku-Mahamud, Ku Ruhana, Abdul Nasir, Husna Jamal

    Published 2010
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  11. 11
    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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  12. 12
    Application of intelligence based genetic algorithm for job sequencing problem on parallel mixed-model assembly line

    Application of intelligence based genetic algorithm for job sequencing problem on parallel mixed-model assembly line by Noroziroshan, Alireza, Mohd Ariffin, Mohd Khairol Anuar, Ismail, Napsiah

    Published 2010
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  13. 13
    Job recruiting system using sorting Algorithm / Adi Asyraf Ayob

    Job recruiting system using sorting Algorithm / Adi Asyraf Ayob by Ayob, Adi Asyraf

    Published 2020
    “…The sorting algorithm will assist the recruiters in selecting best job candidate by assigning score to each applicants and sort the applicant list by the finest score value. …”
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  14. 14
    Flexible job shop scheduling using priority heuristics and genetic algorithm

    Flexible job shop scheduling using priority heuristics and genetic algorithm by Farashahi, Hamid Ghaani

    Published 2010
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  15. 15
    DESIGN AND EVALUATION OF RESOURCE ALLOCATION AND JOB SCHEDULING ALGORITHMS ON COMPUTATIONAL GRIDS

    DESIGN AND EVALUATION OF RESOURCE ALLOCATION AND JOB SCHEDULING ALGORITHMS ON COMPUTATIONAL GRIDS by MEHMOOD SHAH, SYED NASIR

    Published 2012
    “…The issue is not only to develop new algorithms, but also to evaluate them on an experimental computational grid, using synthetic and real workload traces, along with the other existing job scheduling algorithms. …”
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  16. 16
    Benchmark simulator with dynamic environment for job scheduling in grid computing

    Benchmark simulator with dynamic environment for job scheduling in grid computing by Ku-Mahamud, Ku Ruhana

    Published 2014
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  17. 17
    Experimental performance analysis of job scheduling algorithms on computational grid using real workload traces

    Experimental performance analysis of job scheduling algorithms on computational grid using real workload traces by Shah, S.N.M., Mahmood, A.K., Rubab, S., Hassan, M.F.

    Published 2017
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  18. 18
    Low and high level hybridization of ant colony system and genetic algorithm for job scheduling in grid computing

    Low and high level hybridization of ant colony system and genetic algorithm for job scheduling in grid computing by Alobaedy, Mustafa Muwafak, Ku-Mahamud, Ku Ruhana

    Published 2015
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  19. 19
    A Modified Giffler and Thompson Genetic Algorithm on the Job Shop Scheduling Problem

    A Modified Giffler and Thompson Genetic Algorithm on the Job Shop Scheduling Problem by Lee, Hui Peng, Salim, Sutinah

    Published 2006
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  20. 20
    Strategic oscillation for exploitation and exploration of ACS algorithm for job scheduling in static grid computing

    Strategic oscillation for exploitation and exploration of ACS algorithm for job scheduling in static grid computing by Alobaedy, Mustafa Muwafak, Ku-Mahamud, Ku Ruhana

    Published 2015
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