The Relaxation of Complementary Slackness Conditions as a Regularization Method for Optimal Control Problems

Authors

  • S. Radionov National Research University Higher School of Economics; Federal Research Center “Computer Science and Control”; Financial Research Institute of the Ministry of Finance of the Russian Federation
  • N. Pilnik National Research University Higher School of Economics; Federal Research Center “Computer Science and Control”; Financial Research Institute of the Ministry of Finance of the Russian Federation
  • I. Pospelov Federal Research Center “Computer Science and Control”

DOI:

https://doi.org/10.25728/assa.2019.19.2.708

Keywords:

optimal control, complementary slackness conditions, banking system

Abstract

A new approach to the transformation of solutions of optimal control problems based on the special form of relaxation of complementary slackness conditions is presented. The proposed approach is tested on the Russian banking system model, which is derived as a solution of a linear nonautonomous optimization problem with mixed constraints. It is shown that the use of this method regularizes the model in a sense it becomes applicable for the forecasting of the main Russian banking indicators.

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Published

2019-07-01

How to Cite

Radionov, S., Pilnik, N., & Pospelov, I. (2019). The Relaxation of Complementary Slackness Conditions as a Regularization Method for Optimal Control Problems. Advances in Systems Science and Applications, 19(2), 44–62. https://doi.org/10.25728/assa.2019.19.2.708

Issue

Vol. 19 No. 2 (2019): Advances in Systems Science and Applications

Section

Articles