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In heterogeneous system task scheduling is a critical problem because tasks are distributed in many networks; the scheduling problem is known to be NP-complete. The task scheduling problem is the problem of assigning the tasks in the system in a manner that will optimize the overall performance of the application, while assuring the correctness of the result. In this paper, the authors introduce the compact Genetic Algorithm (cGA) to solve the task scheduling problem in heterogeneous system. The cGA represent the population as a probability distribution over the set of solution. It processes each gene independently and requires less memory then the simple genetic algorithm.
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