Search Results - parallel satisfaction ((_ algorithm) OR (based algorithm))*

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  1. 1
    GPU-based odd and even hybrid string matching algorithm

    GPU-based odd and even hybrid string matching algorithm by Rahbari, Ghazal, Abdul Rashid, Nur’Aini, Husain, Wahidah

    Published 2016
    “…String matching is considered as one of the fundamental problems in computer science.Many computer applications provide the string matching utility for their users, and how fast one or more occurrences of a given pattern can be found in a text plays a prominent role in their user satisfaction.Although numerous algorithms and methods are available to solve the string matching problem, the remarkable increase in the amount of data which is produced and stored by modern computational devices demands researchers to find much more efficient ways for dealing with this issue.In this research, the Odd and Even (OE) hybrid string matching algorithm is redesigned to be executed on the Graphics Processing Unit (GPU), which can be utilized to reduce the burden of compute-intensive operations from the Central Processing Unit (CPU).In fact, capabilities of the GPU as a massively parallel processor are employed to enhance the performance of the existing hybrid string matching algorithms.Different types of data are used to evaluate the impact of parallelization and implementation of both algorithms on the GPU. …”
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  2. 2
    Scheduling Problem with Fuzzy Due-dates on Unrelated Parallel Processors

    Scheduling Problem with Fuzzy Due-dates on Unrelated Parallel Processors by Kanesan , Muthusamy, Ishii, Hiroaki

    Published 2000
    “…We propose an efficient algorithm for this problem. (Abstract by authors)…”
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  3. 3
    ROA-CONS: raccoon optimization job scheduling

    ROA-CONS: raccoon optimization job scheduling by Koohi, Sina Zangbari, Abdul Hamid, Nor Asilah Wati, Othman, Mohamed, Ibragimov, Gafurjan

    Published 2021
    “…An optimised schedule results in greater efficiency of the parallel machine. In addition, processes and network heterogeneity is another difficulty for the scheduling algorithm. …”
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    Article
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  4. 4
    Local search approaches for patient scheduling problem in parallel operating theatre

    Local search approaches for patient scheduling problem in parallel operating theatre by Alimin, Nur Neesha

    Published 2020
    “…Patient scheduling in operating theatres (OT) involves high costs to hospitals and may affect treatment and satisfaction to patients. Scheduling for patients in parallel OT can help to schedule a large number of patients and emergency patients are considered in this study .Other than that, emergency patients are able to be scheduled and treated on the day as the modification of schedule is performed during the dynamic processof scheduling. …”
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    Thesis
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  5. 5
    Development of appoinment scheduling agent using distributed constraint satisfaction (DisCS)

    Development of appoinment scheduling agent using distributed constraint satisfaction (DisCS) by Mohd. Azmi, Nurulhuda Firdaus, Eri, Zeti Darleena, Ibrahim, Nuzulha Khilwani, Ahmad Rusli, Rozana Diana

    Published 2008
    “…A reservation environment typically refers to a parallel -machine with n jobs available for processing. …”
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    Monograph
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  6. 6
    Adaptive resource allocation for reliable performance in heterogeneous distributed systems.

    Adaptive resource allocation for reliable performance in heterogeneous distributed systems. by Hussin, Masnida, Abdullah, Azizol, K. Subramaniam, Shamala

    Published 2013
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  7. 7
    Efficient Numerical Modelling of Extreme Wave

    Efficient Numerical Modelling of Extreme Wave by Tan , Vi Nie

    Published 2020
    “…Future works will be carried out to study the parallelization of the algorithm to allow for larger problem size to be treated.…”
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    Final Year Project
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  8. 8
    Efficient Numerical Modelling of Extreme Waves

    Efficient Numerical Modelling of Extreme Waves by Tan, Vi Nie

    Published 2020
    “…Future works will be carried out to study the parallelization of the algorithm to allow for larger problem size to be treated.…”
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