Search Results - (( initial solution using algorithm ) OR ( java application optimization algorithms ))

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  1. 1

    Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

    Published 2012
    “…The algorithm consists of three new mechanisms that organize the work of an ant colony i.e. initial pheromone value mechanism, resource selection mechanism and pheromone update mechanism. …”
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    Monograph
  2. 2

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

    Published 2011
    “…A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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    Thesis
  3. 3

    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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    Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

    Published 2016
    “…These results suggests that optimal algorithms may turn to be non-optimal when practically implemented, unlike USG which reveals far less scheduling overhead and hence could be practically implemented in real-world applications. …”
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    Conference or Workshop Item
  6. 6

    Route Optimization System by Zulkifli, Abdul Hayy

    Published 2005
    “…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
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    Final Year Project
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    Design and statistical analysis of initial solution construction approach in curriculum based course timetabling problem by Wahid, Juliana, Mohd Hussin, Naimah

    Published 2017
    “…To produce a population of initial solution require algorithm that can produce multiple feasible solutions and these solutions must be diverse. …”
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    Conference or Workshop Item
  10. 10

    Combining approximation algorithm with genetic algorithm at the initial population for NP-complete problem by Razip, H., Zakaria, M.N.

    Published 2018
    “…In Genetic Algorithm (GA), the prevalent approach to population initialization are heuristics and randomization. …”
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    Article
  11. 11

    Hybrid tabu search – strawberry algorithm for multidimensional knapsack problem by Wong, Jerng Foong

    Published 2022
    “…The Greedy heuristics by ratio was employed to construct an initial solution. Next, the solution was enhanced by using the hybrid TS-SBA. …”
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    Thesis
  12. 12

    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
  13. 13

    Enhancing the RC4 algorithm by eliminating the Initiative Vector (IV) transmission by Waleed Abdelrahman Yousif Mohammed, Salmah Fattah, Khalid Mohammed Osman Saeed, Ashraf Osman Ibrahim Elsayed, Safaa Eltahier

    Published 2025
    “…This paper introduces an innovative approach to address the vulnerabilities of the RC4 encryption algorithm by employing an Initiative Vector (IV). The proposed method incorporates a lengthy random text without transmitting an initialization vector. …”
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    Article
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    Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

    Published 2012
    “…Moreover, experiments demonstrate that final clustering solution generated by the proposed incremental genetic-based clustering ensemble algorithm using the pattern ensemble learning method possess comparative or better clustering accuracy than clustering solutions generated by the incremental genetic-based clustering ensemble algorithms using other recombination operators. …”
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    Thesis
  16. 16

    Hybrid of firefly algorithm and pattern search for solving optimization problems by Wahid, Fazli, Ghazali, Rozaida

    Published 2018
    “…In the first stage, the parameters of standard FA are initialized. In the firefly changing position stage, the randomization factor is used to update the solution in each iteration of operational stages. …”
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    Article
  17. 17

    Initialization Methods For Conventional Fuzzy C-Means And Its Application Towards Colour Image Segmentation by Tan , Khang Siang

    Published 2011
    “…Due to its capability in providing a particularly promising solution to clustering problems, the conventional Fuzzy C-Mean (FCM) algorithm is widely used as a segmentation method. …”
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    Thesis
  18. 18

    Vehicle Routing Problem with Simultaneous Pickup and Delivery by Sze, San Nah, Sek, Siaw Ying Doreen, Sze, Jeeu Fong, Cheah, Wai Shiang, Chiew, Kang Leng

    Published 2020
    “…A simple heuristic is used to generate the initial solution in the first phase. …”
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    Article
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    Examination timetabling using genetic algorithm case study: KUiTTHO by Mohd Salikon, Mohd Zaki

    Published 2005
    “…Genetic Algorithm (GA) is one of the most popular optimization solutions. …”
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    Thesis
  20. 20

    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
    “…Conclusion/Recommendations: The results obtained from intelligence based genetic algorithm were used as an initial point for fine-tuning by simulated annealing to increase the quality of solution. …”
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    Article