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Management of Control Impacts Based on Maximizing the Spread of Influence

Abstract

The choice of fulcrums for control of socio-economic systems represented by directed weighted signed graphs is a topic of current interest. This article proposes a new method for identifying nodes of impact and influential nodes, which will provide a guaranteed positive system response over the growth model. The task is posed as an optimization problem to maximize the ratio of the norms of the accumulated increments of the growth vector and the exogenous impact vector. The algorithm is reduced to solving a quadratic programming problem with nonlinear restrictions. The selection of the most effective vertices is based on the cumulative gains of the component projections onto the solution vector. Numerical examples are provided to illustrate the effectiveness of the proposed method.

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Acknowledgements

This research was supported by the Russian Foundation for Basic Research (No. 17-01-00076).

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Correspondence to Larisa Tselykh.

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Recommended by Associate Editor Dong-Ling Xu

Alexander Tselykh received the Ph. D. degree in applied mathematics from Rostov State University, Russia in 1990 and became a full professor of computer science in 2000. His research interests include expert systems, decision making, fuzzy sets, mathematical methods and algorithms.

Vladislav Vasilev received the Ph. D. degree in applied mathematics from Rostov State University, Russia in 1997. His research interests include optimization methods, math modelling, and computational mathematics.

Larisa Tselykh received the Ph. D. degree in economics from Rostov State University of Economics, Russia in 2006. Her research interests include expert systems, decision making, mathematical methods and algorithms.

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Tselykh, A., Vasilev, V. & Tselykh, L. Management of Control Impacts Based on Maximizing the Spread of Influence. Int. J. Autom. Comput. 16, 341–353 (2019). https://doi.org/10.1007/s11633-018-1167-2

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  • DOI: https://doi.org/10.1007/s11633-018-1167-2

Keywords

  • Directed weighted graphs
  • control impact
  • spread of influence
  • optimization algorithm
  • growth model