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Grid Computing aims to allow unified access to data, computing power, sensors and other resources through a single virtual laboratory. The development or adaptation of applications for Grid environments is being challenged by the need of scheduling a large number of tasks and resources efficiently. The general problem of optimally mapping tasks to machines in a heterogeneous computing suite has been shown to be NP-complete. In this paper we propose a modified simulated annealing algorithm for scheduling independent tasks in Grid environment. Experimental results show that our proposed algorithm improves the performance of static instances compared to the results of other algorithms reported in the literature.