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Extensive computational simulations and comparisons on 10 different benchmark problems from the literature were carried out.
The accuracy and efficiency of the developed technology is evaluated by application to benchmark problems from the literature.
Experimental results on 358 benchmark problems from the literature show that the suggested method is highly efficient and competitive.
Here a modified genetic algorithm using quasi-random sequences in the initial population is tested by solving a large number of continuous benchmark problems from the literature.
Therefore, authors further extended their work to develop a VNS algorithm for the RAP and tested a set of well-known benchmark problems from the literature.
To test the performance of this new approach, twenty different well-known classification dataset benchmark problems from the UCI dataset were used.
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The method is applied to an 18-panel benchmark problem from the literature with convincing results.
First, a verification of the algorithms used to implement the techniques is carried out using a benchmark problem from the literature.
Our final example is a benchmark problem from the EnKF literature.
A well-known benchmark problem from the PF literature [6] is used.
The performance of the proposed algorithm is tested with benchmark problems from open literature and the results are compared with the existing methods.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.
Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com