Advertisement

Analysis of Business Process Execution Time with Queueing Theory Models

  • Konstantin Samouylov
  • Yuliya Gaidamaka
  • Elvira ZaripovaEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 638)

Abstract

In the paper an approach to the analysis of business process efficiency is proposed. A method for the estimation of a business process execution time as an important performance measure of business processes efficiency is developed. It represents a combination of queuing networks modelling and simplex algorithm of linear programming. The method allows the calculating of the minimum business processes execution time. A method of optimizing activity of the telecommunication company at a predetermined threshold for the business processes execution time is given. The developed technique was illustrated with an end-to-end business process flow “Request-to-Answer” with initial data close to reality.

Keywords

Optimization Business process Queueing theory Execution time Delay Simplex algorithm 

References

  1. 1.
    van der Aalst, W.M.P., Christian, S.: Modeling Business Processes: A Petri Net-oriented Approach, pp. 1–386. The MIT Press, London (2011)zbMATHGoogle Scholar
  2. 2.
  3. 3.
    Sidnev, A., Tuominen, J., Krassi, B.: Business process modeling and simulation. Helsinki University of Technology. Industrial Information Technology Laboratory Publications, pp. 1–116 (2005)Google Scholar
  4. 4.
    ARIS Business Simulator. www.ariscommunity.com/business-process-simulation. Accessed 01 Apr 2016
  5. 5.
    Baskett, F., Chandy, K.M., Muntz, R.R., Palacios, F.G.: Open, closed, and mixed networks of queues with different classes of customers. J. ACM 22(2), 248–260 (1975)MathSciNetCrossRefzbMATHGoogle Scholar
  6. 6.
    Ficken, F.A.: The Simplex Method of Linear Programming. Dover Books, New York (2015)zbMATHGoogle Scholar
  7. 7.
    Mantepu, T.M., Solly, M.S.: Modelling and measuring milestones in business process optimization. Probl. Persp. Manage. 12(4), 221–224 (2014)Google Scholar
  8. 8.
    TeleManagement Forum. Enhanced Telecom Operations (eTOM) The Business Process Framework. www.tmforum.org. Accessed 01 May 2016
  9. 9.
    Business Process Model and Notation (BPMN). Version 2.0.2: OMG Document Number: formal.2013-12-09. Object Management Group (2013)Google Scholar
  10. 10.
    Business process framework (eTOM). End-to-end business flows. GB921 Addendum E. R15.0.0., pp. 1–110 (2016)Google Scholar
  11. 11.
    Moiseeva, S.P., Zakhorolnaya, I.A.: Mathematical model of parallel retrial queueing of multiple requests. Optoelectron. Instrum. Data Process. 47(6), 567–572 (2011)CrossRefGoogle Scholar
  12. 12.
    Nazarov, A.A., Moiseev, A.N.: Distributed system of processing of data of physical experiments. Russ. Phys. J. 57(7), 984–990 (2014)CrossRefGoogle Scholar
  13. 13.
    Bakholdina, M., Gortsev, A.: Joint probability density of the intervals length of modulated semi-synchronous integrated flow of events in conditions of a constant dead time and the flow recurrence conditions. In: Dudin, A., Nazarov, A., Yakupov, R., Gortsev, A. (eds.) ITMM 2014. CCIS, vol. 564, pp. 13–27. Springer, Heidelberg (2015). doi: 10.1007/978-3-319-25861-4_2 Google Scholar
  14. 14.
    Samouylov, K.E., Chukarin, A.V., Yarkina, N.V.: Business Processes and Information Technology in the Management of Telecommunications Companies, pp. 1–619. Alpina-Publishers, Randwick (2016)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Konstantin Samouylov
    • 1
  • Yuliya Gaidamaka
    • 1
  • Elvira Zaripova
    • 1
    Email author
  1. 1.Department of Applied Probability and InformaticsRUDN UniversityMoscowRussian Federation

Personalised recommendations