Search Results - (( web application ant algorithm ) OR ( job application ((bees algorithm) OR (based algorithm)) ))

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  1. 1
    Quantum Particle Swarm Optimization Technique for Load Balancing in Cloud Computing

    Quantum Particle Swarm Optimization Technique for Load Balancing in Cloud Computing by Elrasheed Ismail, Sultan

    Published 2013
    “…Secondly, this thesis proposes job-combination based static algorithm for load balancing where all jobs should organized into the standard job combinations, each task of which consists of one to four jobs. …”
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  2. 2
    A new ant based rule extraction algorithm for web classification

    A new ant based rule extraction algorithm for web classification by Ku-Mahamud, Ku Ruhana, Saian, Rizauddin

    Published 2011
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  3. 3
    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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  4. 4
    Comparison of attribute selection methods for web texts categorization

    Comparison of attribute selection methods for web texts categorization by Saian, Rizauddin, Ku-Mahamud, Ku Ruhana

    Published 2010
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  5. 5
    Comparison Between the Bees Algorithm and Genetic Algorithm Model in Manpower Allocation on Cell Loading Problem

    Comparison Between the Bees Algorithm and Genetic Algorithm Model in Manpower Allocation on Cell Loading Problem by AlMahasneh, Hossam Sayel

    Published 2010
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  6. 6
    Bee foraging behaviour techniques for grid scheduling problem

    Bee foraging behaviour techniques for grid scheduling problem 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.These resources are collected together to make a huge computing power.Job scheduling problem is one of the key issues in grid computing and failing to look into grid scheduling results in uncompleted view of the grid computing.Achieving optimized performance of grid system, and matching application requirements with available computing resources, are the objectives of grid job scheduling.Bee colony approaches are more adaptive to grid scheduling due to high heterogeneous and dynamic nature of resources and applications in grid.These algorithms have shown encouraging results in terms of time and cost.This paper presents some resent research activities inspired by bee foraging behavior for grid job scheduling especially ABC and BCO approaches.Different original studies related to this area are briefly described along with their comparisons against them and results.The review summary of their derived algorithms and research efforts is done.…”
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  7. 7
    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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  8. 8
    A priority based job scheduling algorithm in cloud computing

    A priority based job scheduling algorithm in cloud computing by Shamsollah, Ghanbari, Othman, Mohamed

    Published 2012
    “…Some intensive researches have been done in the area of job scheduling of cloud computing. In this paper we have proposed a new priority based job scheduling algorithm (PJSC) in cloud computing. …”
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  9. 9
    Adaptive intelligence job online scheduling within dynamic grid environment based on gridsim

    Adaptive intelligence job online scheduling within dynamic grid environment based on gridsim by Lorpunmanee, Siriluck, Md. Sap, Mohd. Noor, Abdullah, Abdul Hanan

    Published 2008
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  10. 10
    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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  11. 11
    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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  12. 12
    Job position prediction based on skills and experience using machine learning algorithm / Ezaryf Hamdan

    Job position prediction based on skills and experience using machine learning algorithm / Ezaryf Hamdan by Hamdan, Ezaryf

    Published 2024
    “…Accessible through a desktop application, the Job Position Prediction System prioritizes userfriendliness for job seekers. …”
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  13. 13
    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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  14. 14
    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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  15. 15
    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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  16. 16
    A conflict-based priority dispatching rule and operation-based approaches to job shops

    A conflict-based priority dispatching rule and operation-based approaches to job shops by Dominic P, Dhanapal Durai, Kaliamoorthy, S, Murugan, R

    Published 2004
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  17. 17
    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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  18. 18
    Task scheduling in cloud computing using hybrid genetic algorithm and bald eagle search (GA-BES)

    Task scheduling in cloud computing using hybrid genetic algorithm and bald eagle search (GA-BES) by Kamal Khairi Supaprhman

    Published 2022
    “…As for the running method the compilation of the code will be run by using cmd and Ant Apache and the total average result of 30 simulation will be view on the web base application will be run using xampp.…”
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  19. 19
    Application of an evolutionary algorithm-based ensemble model to job-shop scheduling

    Application of an evolutionary algorithm-based ensemble model to job-shop scheduling by Tan, Choo Jun, Neoh, Siew Chin, Lim, Chee Peng, Hanoun, Samer, Wong, Wai Peng, Loo, Chu Kiong, Zhang, Li, Nahavandi, Saeid

    Published 2019
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  20. 20
    Task scheduling in cloud computing environment using hybrid genetic algorithm and bat algorithm

    Task scheduling in cloud computing environment using hybrid genetic algorithm and bat algorithm by Muhammad Syahril Mohamad Sainal

    Published 2022
    “…Furthermore, CloudSim simulator will be used to evaluate the performance of this algorithm. The result of the algorithm performance will be appeared in web application system. …”
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