Abstract
In the conditions of digitalization, where the flow of various kinds and volumes of information is large, one has to face optimization problems of large dimension or so-called "large systems". A great potential for increasing efficiency lies in the use of computations to solve large-dimensional problems with a special, but often occurring structure. In the current work, the Danzig-Wolfe decomposition method is considered as one of the universal methods for solving a class of large-dimensional problems, since most real economic problems have a block structure of the constraint matrix or are reduced to such kinds of problems by some transformations. The paper hypothesizes that the decomposition method can be used not only for problems of large dimension, but also for problems with a relatively small number of variables and constraints under conditions of uncertainty of initial data.
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