Sentence examples for cross decomposition from inspiring English sources

The formulation of proposed model uses the concept of cross decomposition approach.

This paper proposes a new cross decomposition method, where BD and DWD are combined in a unified framework to improve the solution of scenario based two-stage stochastic MILPs.

When first-stage variables are mixed-integer and second-stage variables are continuous, these MILPs can be solved efficiently by classical decomposition methods, such as Dantzig/Wolfe decomposition (DWD), Lagrangian decomposition, and Benders decomposition (BD), or a cross decomposition strategy that combines some of the classical decomposition methods.

Case study of two different supply chain systems, a bioproduct supply chain and an industrial chemical supply chain, show that the proposed cross decomposition method has significant computational advantage over BD and the monolith approach, when the number of scenarios is large.

To solve the optimization problem, the authors apply the mean value cross-decomposition method, which results in an implementation-friendly solution.

(Such is the strength of (P.6), a genuine cross between decomposition and composition principles).

This abstraction supports cross-system decomposition as well as composition of interaction patterns for the purpose of emergent behavior.

The color overlays show 5 example RSNs (coded in different colors) from the 3 different acquisitions of subject 2, presented as z-statistic images (from a multiple regression against a 100-component cross-TR decomposition of the datasets—see Methods for details), thresholded at Z>4 in all cases.

We prove that II1 factors M have a unique (up to unitary conjugacy) cross-product type decomposition around "core subfactors" N⊂M satisfying the property HT of [S. Popa, On a class of type II1 factors with Betti numbers invariants, Ann. of Math. (2) 163 (2006) 809–899] and a certain "torsion freeness" condition.

They employ a new Bayesian method for analysis of diallel crosses that improves decomposition of phenotypic variance into biologically intuitive components (Lenarcic et al. 2012).

In order to take full advantage of the data relating not only to the aggregate factors used in the Kaya factorization, but their composition, we then conduct a cross-country Index Decomposition Analysis on the difference in CO2 emissions between Austria and Czechoslovakia.