Search Results - (( initial solution scheduling algorithm ) OR ( java application based algorithm ))

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  1. 1

    Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

    Published 2011
    “…Experimental results show that EACO produced better grid resource management solution compared to other algorithms. …”
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    Thesis
  2. 2

    Batch mode heuristic approaches for efficient task scheduling in grid computing system by Maipan-Uku, Jamilu Yahaya

    Published 2016
    “…We simulate our proposed algorithms using a Java based simulator that is purposedly built for Grid computing simulations. …”
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    Thesis
  3. 3

    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
  4. 4

    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
  5. 5

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

    Published 2010
    “…In the next method, a genetic algorithm has been developed. It has been shown that proposed genetic algorithm with a reinforced initial population (GA2) has better efficiency compared to a proposed genetic algorithm with fully random initial population (GA0). …”
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    Thesis
  6. 6

    A branch and bound and simulated annealing approach for job shop scheduling by Tan, Hui Woon, Salim, Sutinah

    Published 2004
    “…In the branch and bound approach, the job shop scheduling problem is represented by a disjunctive graph, then the optimal schedule is obtained using the branch and bound algorithm while simulated annealing is a local search based algorithm which will slightly perturb the initial feasible solution to decrease the makespan. …”
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    Article
  7. 7

    Hybrid dynamic scheduling model for flexible manufacturing system with machine availability and new job arrivals by Paslar, Shahla

    Published 2015
    “…The performance of the schedules as produced by the scheduling/rescheduling algorithms were investigated and compared. …”
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    Thesis
  8. 8

    A hybrid genetic algorithm for optimization of scheduling workflow applications in heterogeneous computing systems by Ahmad, S.G., Liew, Chee Sun, Munir, E.U., Ang, Tan Fong, Khan, S.U.

    Published 2016
    “…These features are incorporated in the proposed Hybrid Genetic Algorithm (HGA). A solution obtained from a heuristic is seeded in the initial population that provides a direction to reach an optimal (makespan)solution. …”
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    Article
  9. 9

    Hybrid genetic algorithm with multi-parents recombination for job shop scheduling problems / Ong Chung Sin by Ong, Chung Sin

    Published 2013
    “…The chromosomes are decoded into active schedules thus increasing the probability of obtaining near or optimal solution significantly. …”
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    Thesis
  10. 10

    Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling by Anuar, Nurul Izah

    Published 2022
    “…This research first proposes an improved continuous MOPSO to address the rapid clustering problem that exists in the basic PSO algorithm using three improvement strategies: re-initialization of particles, systematic switch of best solutions and mutation on global best selection. …”
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    Thesis
  11. 11

    A Modified LRE-TL Real-Time Multiprocessor Scheduling Algorithm by Alhussian, Hitham, Zakaria, Mohd Nordin, Hussin, Fawnizu Azmadi, Bahbouh, Hussein T

    Published 2013
    “…A modified version of Local Remaining Execution-TL (LRE-TL) real-time multiprocessor scheduling algorithm is presented. LRE-TL uses two events to make scheduling decisions: The Bottom (B) event and the Critical (C) event. …”
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    Conference or Workshop Item
  12. 12

    Max-average: an extended max-min scheduling algorithm for Grid computing environtment by Maipan-uku, J. Y., Muhammed, Abdullah, Abdullah, Azizol, Hussin, Masnida

    Published 2016
    “…This paper presents a new proposed grid based scheduling algorithm called Max-Average, inspired from Max-Min algorithm. …”
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    Article
  13. 13

    A modified LRE-TL real-time multiprocessor scheduling algorithm by Alhussian, H., Zakaria, N., Hussin, F.A., Bahbouh, H.T.

    Published 2014
    “…A modified version of Local Remaining Execution-TL (LRE-TL) real-time multiprocessor scheduling algorithm is presented. LRE-TL uses two events to make scheduling decisions: The Bottom (B) event and the Critical (C) event. …”
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    Article
  14. 14

    Vehicle pick-up and drop-off schedule optimization in a university setting by Teo, Chun Kit

    Published 2024
    “…A simulated annealing-based multi-directional iterative local search algorithm is employed for solution optimization. The initial solution is generated by distributing requests across vehicles, and local searches are performed through request swapping and movement. …”
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    Final Year Project / Dissertation / Thesis
  15. 15

    Reducing Tasks Migration in LRE-TL Real-time Multiprocessor Scheduling Algorithm by Alhussian, Hitham, Nordin, Zakaria M, Hussin, Fawnizu Azmadi, Bahbouh, Hussein T.

    Published 2013
    “…In this paper we present a modification of Local Remaining Execution (LRE-TL) real-time multiprocessor scheduling algorithm to reduce tasks migration significantly. …”
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    Conference or Workshop Item
  16. 16

    Hybrid genetic algorithm for uncapacitated university examination timetabling problem by Ishak, Suhada

    Published 2015
    “…This study presents a solution for an uncapacitated UETP where five domain-specific knowledges in the form of low-level heuristics are used to guide the construction of the timetable in the initial population. …”
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    Thesis
  17. 17

    Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures by Koohi, Sina Zangbari

    Published 2020
    “…However, the current meta-heuristic algorithms do not ensure an optimum solution within a reasonable time. …”
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  18. 18

    Parallel multiple tabu search for multiobjective Urban Transit Scheduling Problem by Uvaraja, Vikneswary, Lai, Soon Lee, Abd Rahmin, Nor Aliza, Hsin, Vonn Seow

    Published 2020
    “…A parallel tabu search algorithm was proposed to solve the problem by modifying the initialization process and incorporating intensification and diversification approaches to guide the search effectively from the different feasible domain in finding optimal solutions with lesser computational effort. …”
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    Article
  19. 19

    Partial examination assignment approaches for solving examination timetabling problems by Mandal, Ashis Kumar

    Published 2016
    “…However, these traditional approaches bias toward the initial timetable where the improvement algorithms (sometimes) are affected and unable to produce a quality timetable. …”
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  20. 20

    Web based personalized university timetable for UiTM students using genetic algorithm / Mohd Radhi Fauzan Jamli and Ahmad Firdaus Ahmad Fadzil by Jamli, Mohd Radhi Fauzan, Ahmad Fadzil, Ahmad Firdaus

    Published 2024
    “…The research endeavors to develop a web-based system specifically designed to create personalized university timetables for Universiti Teknologi MARA (UiTM) students using genetic algorithms, aiming to address the urgent need for a customizable timetable solution catering to the diverse scheduling requirements of both repeater and non-repeater students while optimizing course group selection to minimize conflicts and enhance scheduling flexibility. …”
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    Article