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Dispatching rules play an important role especially in semiconductor manufacturing scheduling, because these fabrication facilities are characterized by high complexity and dynamics. The process of developing and adapting dispatching rules is currently a tedious, largely manual task. Coupling Genetic Programming (GP), a global optimization meta-heuristic from the family of Evolutionary Algorithms,...
The prediction of fill levels in stormwater tanks is an important practical problem in water resource management. In this study state-of-the-art CI methods, i.e., Neural Networks (NN) and Genetic Programming (GP), are compared with respect to their applicability to this problem. The performance of both methods crucially depends on their parametrization. We compare different parameter tuning approaches,...
The paper suggests a customized elite based genetic programming technique for the identification of complex nonlinear systems. The models generated by the proposed method are nonlinear, linear in parameters, as the universal approximation capacities of such a mathematical formalism have been rigorously proven. To better exploit the models' parameter wise linearity, the authors propose a memetic approach...
An elitist multiobjective optimization methodology, based on genetic programming, is suggested in the following, as means of identifying complex nonlinear systems. The structure and parameters of the nonlinear models are selected simultaneously as result of the conjoint usage of customized genetic operators and of a deterministic parameter computation procedure. This symbiosis is configured to efficiently...
We proposed a genetic programming (GP) based method for automated optimization design of base station configuration plans of 3G wireless networks. This method aims to address the disadvantages of the current methods on wireless network optimization and to satisfy new requirements for network design. Evolutional topological operators and terminal set are designed for GP the Prim is used to guide the...
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