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We present a Benders decomposition-based solution algorithm together with several algorithmic enhancements for this problem.
Deposits of polydispersed, spherical particles were generated by several algorithmic models, which simulate different deposition conditions.
In this paper, we investigate several algorithmic and complexity-theoretic topics regarding Tarski's fixed point theorem.
We study the parallelization of these kernels using several algorithmic variants: either iterative or recursive and using different splitting strategies.
The procedure aims at solving large-scale instances by incorporating several algorithmic strategies that helped reduce the problem size.
Several algorithmic and computational aspects of the method, including computation of the electrostatics terms and parallelization are discussed.
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Sra works on several theoretical, algorithmic, and applied questions in machine learning and data science.
Based on this, several new algorithmic strategies for computing the eigenvector efficiently are motivated and designed.
In this study, several detailed algorithmic schemes are presented along with related computational aspects associated with Granular Computing.
This setting gives rise to several different algorithmic questions, depending on the nature of time (discrete/continuous), the property asked (stability/stabilizability), or the type of uncertainty (fixed/switching).
Based on the information used, several different algorithmic definitions of aromaticity can be defined.
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