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GENETIC A LGORITHM FOR MULTIPROCESSOR TASK SCHEDULING

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Author(s): Ritu Verma | Sunita Dhingra

Journal: International Journal of Computer Science and Management Studies
ISSN 2231-5268

Volume: 11;
Issue: 02;
Start page: 181;
Date: 2011;
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Keywords: Genetic Algorithm (GA) | crossover | mutation

ABSTRACT
Multiprocessor task scheduling (MPTS) is an important andcomputationally difficult problem. Multiprocessors have emergedas a powerful computing means for running real-time applicationsespecially due to limitation of uni-processor system for not havingsufficient enough capability to execute all the tasks. This paperdescribes multiprocessor task scheduling in the form of permutation flow shop scheduling, which has an objective function for minimizing the makespan. Here, we will conclude how the performance of genetic algorithms (value of the makespan of the schedule) varies with the variation of Genetic Algorithm (GA) control parameters (population size, crossover probability and mutation probability).
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