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It has been demonstrated that the algorithm is sufficiently robust in producing similar quality solutions.
It has been demonstrated that the algorithm delivers the theoretically predicted accuracy in both time and space.
A test case demonstrated that the algorithm could minimize impact of timber harvest on an edge-sensitive bird species.
It was demonstrated that the algorithm maintains the accuracy in the case of multiple defects compared to conventional algorithms based on Born approximation.
A case studied is the Na K alloy with MP2/ECP energies, where it is demonstrated that the algorithm is efficient in obtaining global minima.
Additionally, the results demonstrated that the algorithm was slightly sensitive to the parameter settings, with the number of generations presented the most significant effect.
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Various tests demonstrated that the algorithms deliver theoretically predicted accuracy, even for very large interfacial distortions.
By considering test cases previously considered by other researchers, it is also demonstrated that the algorithms do not exhibit spurious solutions.
Experiments over controlled benchmarks demonstrated that the algorithms' performances are problem dependent [50, 51].
Overall, our analysis demonstrated that the algorithms differ in sensitivity and specificity, and users should therefore select their algorithm depending on which performance characteristic is the highest priority.
Analytical and numerical studies demonstrate that the algorithm is stable under subsonic conditions.
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