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Most of the existing approaches utilize both solution quality and convergence rate to perform comparative analysis.
The computations showed promising results in terms of both solution quality and computation time.
Numerical results show that the proposed approach has an acceptable performance in terms of both solution quality and solution time.
On the contrary, with proposed methodology ranking of algorithms is done in terms of both solution quality and convergence rate.
The results of this analysis indicate that the developed heuristic is very e cient in terms of both solution quality and the required CPU time.
We compare our algorithms with the existing best-known algorithm, and show that our approaches out-perform it in terms of both solution quality and execution time.
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The experimental results prove good performance of hybrid algorithm in terms of both the solution quality and computation time.
Comparisons show that the proposed TS out-performs GA solutions, in terms of both the solution quality and the execution time.
The results show that both the solution quality and the convergence speed of the ATPPSO algorithm precede the other two recently proposed algorithms.
Our extensive computational analysis shows that the proposed variable neighborhood search based heuristics outperforms the best-known algorithms in terms of both the solution quality and computational efforts.
Designers using a problem driven design strategy tended to produce the best results in terms of the balance of both overall solution quality and creativity.
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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