High-throughput resource management
The grid
Evolutionary Optimization Techniques on Computational Grids
ICCS '02 Proceedings of the International Conference on Computational Science-Part I
Evolutionary computation: comments on the history and current state
IEEE Transactions on Evolutionary Computation
Enhancing wildland fire prediction on cluster systems applying evolutionary optimization techniques
Future Generation Computer Systems
Enhancing wildland fire prediction on cluster systems applying evolutionary optimization techniques
Future Generation Computer Systems
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Forest fire propagation modeling has typically been included within the category of grand challenging problems due to its complexity and to the range of disciplines that it involves. The high degree of uncertainty in the input parameters required by the fire models/simulators can be approached by applying optimization techniques, which, typically involve a large number of simulation executions, all of which usually require considerable time. Distributed computing systems (or metacomputers) suggest themselves as a perfect platform to addressing this problem. We focus on the tuning process for the ISStest fire simulator input parameters on a distributed computer environment managed by Condor.