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Furthermore, it is demonstrated for realistic large scale grids.
In order to be able to solve the optimization model for realistic large systems, a metaheuristic approach based on evolutionary algorithms is developed.
The method was shown to be efficient for medium size nonlinear problem, but its computational performance for realistic large scale problems was not satisfactory.
Altogether this means that for realistic large processing, there is not one choice that can be made that is "always best" in terms of energy use and associated emissions.
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This is fine if the model is small enough to be visible on the screen in its entirety; it becomes problematic for realistic, larger models.
The set of non-linear equations to be solved for the Fourier coefficients can then be substantially reduced for many realistic large order mechanical systems.
In Section 4, various results obtained by simulations with the deployment tool are discussed for a realistic large-scale disaster scenario in the city center of Ghent, Belgium.
For solving more realistic large-size instances, a variable neighborhood search based heuristic is designed.
With the increasing interest in and the need for plant-wide design and control, it is desirable to develop rigorous models for realistic and large-scale processes with recycle streams, energy integration and non-ideal systems, and use them for evaluating plant-wide control schemes.
It offers two complementary approaches for two different applications: a synthetic model for realization of small-scale or illustrative case studies and a real model for realistic and large-scale heterogeneous network performance evaluation.
Two complementary approaches for two different applications are proposed: a synthetic model for realization of small-scale or illustrative case studies and a real model for realistic and large-scale two-tier network performance evaluation.
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