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Dual Forecasting Algorithm for Technological Structural Matrices in Dynamic Input-Output Models

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Abstract

Based on the global Krotov successive improvement method, we propose a dual computational algorithm for a discrete optimal control problem corresponding to a convex large-scale quadratic programming problem with a separable functional that arises in the prediction of the direct costs (structural) matrix in dynamic input-output models. With decomposition, we are able to use a special form of the constraint matrix to reduce the problem dimension.

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Acknowledgments

The studies presented in this work were started while the author was working at the Trapeznikov Institute of Control Sciences (ICS) of the Russian Academy of Sciences in Laboratory 45 under the supervision of Professor Vadim F. Krotov. The author is grateful to his former co-workers Dr. A.G. Aleksandrov, Dr. O.V. Morzhin, and L.A. Selivanova for their help and discussions of the work.

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Authors and Affiliations

  1. St. Cloud State University, St. Cloud, Minnesota, USA

    P. I. Safonov

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  1. P. I. Safonov
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Correspondence to P. I. Safonov.

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Russian Text © The Author(s), 2019, published in Avtomatika i Telemekhanika, 2019, No. 8, pp. 109–128.

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Safonov, P.I. Dual Forecasting Algorithm for Technological Structural Matrices in Dynamic Input-Output Models. Autom Remote Control 80, 1455–1470 (2019). https://doi.org/10.1134/S0005117919080071

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