Selection of controller parameters using genetic algorithms
Engineering systems with intelligence
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Optimizing the number of airfoils in turbine design using genetic algorithms
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part III
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The evolutionary algorithms can be considered as a powerful and interesting technique for solving large kinds of control problems. However, the great disadvantage of the evolutionary algorithms is the great computational cost. So, the objective of this work is the parallel processing of evolutionary algorithms on a general-purpose architecture (cluster of workstations), programmed with a simple and very well-know technique such as message passing.