Skip to main content

Control Theory Application to Complex Technical Objects Scheduling Problem Solving

  • 946 Accesses

Part of the Advances in Intelligent Systems and Computing book series (AISC,volume 574)

Abstract

We present a new model for optimal scheduling of complex technical objects (CTO). CTO is a networked controlled system that is described through differential equations based on a dynamic interpretation of the job execution. The problem is represented as a special case of the job shop scheduling problem with dynamically distributed jobs. The approach is based on a natural dynamic decomposition of the problem and its solution with the help of a modified form of continuous maximum principle blended with combinatorial optimization.

Keywords

  • Schedule Problem
  • Network Control System
  • Optimal Program Control
  • Complex Technical Object
  • Flow Control Model

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-319-57264-2_17
  • Chapter length: 8 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   189.00
Price excludes VAT (USA)
  • ISBN: 978-3-319-57264-2
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   249.99
Price excludes VAT (USA)

References

  1. Ivanov, D.A., Sokolov, B.V.: Adaptive Supply Chain Management. Springer, Wiley and Sons, New York (2010)

    CrossRef  Google Scholar 

  2. Ivanov, D.A., Sokolov, B.V.: Dynamic supply chain scheduling. J. Schedul. 15(2), 201–216 (2012)

    MathSciNet  CrossRef  MATH  Google Scholar 

  3. Ohtilev, M.Y., Sokolov, B.V., Yusupov, R.M.: Intellectual Technologies for Monitoring and Control of Structure-Dynamics of Complex Technical Objects. Nauka, Moscow (2006)

    Google Scholar 

  4. Kalinin, V.N., Sokolov, B.V.: Optimal planning of the process of interaction of moving operating objects. Int. J. Diff. Eqn. 21(5), 502–506 (1985)

    MATH  Google Scholar 

  5. Chen, Z.L., Pundoor, G.: Order assignment and scheduling in a supply chain. J. Oper. Res. 54, 555–572 (2006)

    MathSciNet  CrossRef  MATH  Google Scholar 

  6. Lee, E.B., Markus, L.: Foundations of Optimal Control Theory. Springer, Wiley and Sons, New York (1967)

    MATH  Google Scholar 

  7. Chernousko, F.L.: State Estimation of Dynamic Systems. SRC Press, Boca Raton (1994)

    MATH  Google Scholar 

Download references

Acknowledgments

The research described in this paper is partially supported by the Russian Foundation for Basic Research (grants 15-07-08391, 15-08-08459, 16-07-00779, 16-08-00510, 16-08-01277, 16-29-09482-ifi-i, 16-07-00925, 17-08-00797, 17-06-00108, 17-01-00139, 17-20-01214), grant 074-U01 (ITMO University), project 6.1.1 (Peter the Great St. Petersburg Politechnic University) supported by Government of Russian Federation, Program STC of Union State “Monitoring-SG” (project 1.4.1-1), state order of the Ministry of Education and Science of the Russian Federation 2.3135.2017/K, state research 0073-2014-0009, 0073-2015-0007.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Inna Trofimova .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Sokolov, B., Trofimova, I., Ivanov, D., Krylov, A. (2017). Control Theory Application to Complex Technical Objects Scheduling Problem Solving. In: Silhavy, R., Senkerik, R., Kominkova Oplatkova, Z., Prokopova, Z., Silhavy, P. (eds) Cybernetics and Mathematics Applications in Intelligent Systems. CSOC 2017. Advances in Intelligent Systems and Computing, vol 574. Springer, Cham. https://doi.org/10.1007/978-3-319-57264-2_17

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-57264-2_17

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-57263-5

  • Online ISBN: 978-3-319-57264-2

  • eBook Packages: EngineeringEngineering (R0)