Search Results - (( java application scheduling algorithm ) OR ( next optimization method algorithm ))

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  1. 1

    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
  2. 2

    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
  3. 3

    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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    Thesis
  4. 4

    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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    Thesis
  5. 5

    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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    Thesis
  6. 6

    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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    Thesis
  7. 7

    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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    Article
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    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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    Thesis
  10. 10

    VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern by Angeline Teoh, Szu Fern

    Published 2012
    “…Two methods of optimization are used for CBLL. They are Cross Entropy and also Genetic Algorithm. …”
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    Thesis
  11. 11

    The application of queuing theory model using the DSW Algorithm and the L-R Method to optimize customer flow at Pizza Hut / Anis Natasha Mohamad Nizam, Nurfatihah Nadirah Noor Azla... by Mohamad Nizam, Anis Natasha, Noor Azlan, Nurfatihah Nadirah, Fazli, Nur Izzati Aliah

    Published 2022
    “…This study aims to compare the behaviors of a queuing system at an order counter using the Fuzzy Queuing Model, which are the Dong, Shah, and Wong (DSW) Algorithm and the Left-Right (L-R) Method. One of the approximate methods that employs intervals at various a -cuts is the DSW Algorithm. …”
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    Student Project
  12. 12

    Sauvola Segmentation and Support Vector Machine-Salp Swarm Algorithm Approach for Identifying Nutrient Deficiencies in Citrus Reticulata Leaves by Lia, Kamelia

    Published 2024
    “…In the next phase, the datasets are optimized using the Salp Swarm Algorithm (SSA), which improves classification accuracy. …”
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    Thesis
  13. 13

    Performances Of Metaheuristic Algorithms In Optimizing Tool Capacity Allocations by Goheannee

    Published 2014
    “…To achieve the best allocation, optimization methods, such as metaheuristic algorithms are commonly used. …”
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    Thesis
  14. 14

    Optimizing the placement of fire department in Kulim using greedy heuristic and simplex method / Muhammad Abu Syah Mohd Suzaly by Mohd Suzaly, Muhammad Abu Syah

    Published 2023
    “…This iterative process continues until a final solution is reached, which is usually optimal or close to optimal. The next method is simplex method. …”
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    Thesis
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    Optimal overcurrent relay solutions for protection coordination using metaheuristics approaches with penalty function method by Noor Zaihah, Jamal, Mohd Herwan, Sulaiman, Abdul, Nasir, Jabbar, Waheb A.

    Published 2024
    “…The algorithms are assisted with penalty function method during the selection of new agents/ offsprings to confirm the generations that violated the constraints are superseded during the next generation selection. …”
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    Article
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    Optimal parameter estimation of permanent magnet synchronous motor by using Mothflame optimization algorithm / Abdolmajid Dejamkhooy and Sajjad Asefi by Dejamkhooy, Abdolmajid, Asefi, Sajjad

    Published 2018
    “…In the next step, the parameter identification as an optimization problem is solved by Moth-flame optimization, which is a novel nature-inspired heuristic algorithm. …”
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    Article
  19. 19

    A review: accuracy optimization in clustering ensembles using genetic algorithms by Ghaemi, Reza, Sulaiman, Md. Nasir, Ibrahim, Hamidah, Mustapha, Norwati

    Published 2011
    “…It combines multiple partitions generated by different clustering algorithms into a single clustering solution. Genetic algorithms are known as methods with high ability to solve optimization problems including clustering. …”
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    Article
  20. 20

    Ideal combination feature selection model for classification problem based on bio-inspired approach by Basir, Mohammad Aizat, Hussin, Mohamed Saifullah, Yusof, Yuhanis

    Published 2020
    “…The important step is to idealize the combined feature selection models by finding the best combination of search method and feature selection algorithms. The next step is to define an optimized feature set for classification task. …”
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    Book Section