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    A mixed integer linear programming model for real-time task scheduling in multiprocessor computer system by Oluwadare, Samuel Adeboyo, Akinnuli, Basil Oluwafemi

    Published 2012
    “…This may lead to low quality service and deadline misses. The advent of multi-processor systems offers a more efficient way of processing multimedia data in real-time.With the development of appropriate scheduling algorithm, another challenge is the mode of assigning tasks in multi-processor systems.This calls for the use of an appropriate mathematical model that will take cognizance of the nature of variables involved.In this research work, a Mixed Integer Linear Programming Model (MILP) was developed to assign tasks in a multiprocessor system.The MILP model was used to assign tasks to multi-processor systems ranging between 5 and 10 homogeneous processors.The result of the simulation runs shows that with the appropriate scheduling algorithm, a high success rate ratio and guaranteed number of deadlines met could be achieved.…”
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    Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

    Published 2005
    “…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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