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The Comparison of Structured Modeling and Simulation Modeling of Queueing Systems

  • Igor Yakimov
  • Alexander Kirpichnikov
  • Vladimir MokshinEmail author
  • Zuhra Yakhina
  • Rustem Gainullin
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 800)

Abstract

The paper provides the description of 13 structured and simulation modeling systems: AnyLogic, Arena, Bizagi Modeler, Business Studio, Enterprise Dynamics, ExtendSim, Flexsim, GPSS W, Plant Simulation, Process Simulator, Rand Model Designer, Simio Simul8. The routes of dynamic objects movement in modeling systems in structured models built in these SSMS are visually represented. SSMS are compared according to structural models of \(M{\slash }M{\slash }5\) queuing systems obtained in these SSMS and the difference of simulation modeling from analytical modeling results. The reliability was assessed by the values of mathematical expectation and standard deviations of quantity and time indexes. The paper aims to select SSMS for modeling probabilistic objects in conformity with the area the object refers to, consideration of simulation modeling results credibility, and users personal preferences as well.

Keywords

Simulated model Analytical model Queueing system M / M / 5 

References

  1. 1.
    Kindler, E.: The modeling languages. In: Proceedings of the Workshop on Business Process Reference, BPRM (2005)Google Scholar
  2. 2.
    Borshev, A.V.: Simulation modeling: area state in 2015, tendency. In: Studies of the 7th Russian Scientific Practical Conference: Simulation Modeling. Theory and Practice, pp. 14–22 (2015). (in Russian)Google Scholar
  3. 3.
    Yakimov, I.M., Kirpichnokov, A.P., Zainullina, G.P., Yakhina, Z.T.: Validation evaluation of simulation modeling results by analytical modeling findings. Bull. Kazan Techn. Univ. 18(6), 173–178 (2015). Kazan. (in Russian)Google Scholar
  4. 4.
    Yakimov, I.M., Kirpichnikov, A.P., Zainullina, G.P., Isaeva, Y.G., Yakhina, Z.T.: Informational system o simulation and analytical modeling of queueing system. Bull. Kazan Techn. Univ. 19(5), 141–145 (2016). Kazan. (in Russian)Google Scholar
  5. 5.
    Mokshin, V.V., Yakimov, V.V.: System Modeling in AnyLogic: Tutorial Recomendation to Perform Laboratory Work. Shkola Publ., Kazan (2014). (in Russian)Google Scholar
  6. 6.
    Tayfur, A., Melamed, B.: Simulation Modeling and Analysis with ARENA. Elsevier, Inc., Amsterdam (2007)Google Scholar
  7. 7.
    Yue, W., Takahashi, Y., Takagi, H.: Advances in Queueing Theory and Network Applications. Springer, New York (2009). doi: 10.1007/978-0-387-09703-9 CrossRefzbMATHGoogle Scholar
  8. 8.
    Alfa, A.S.: Queueing Theory for Telecommunications. Springer, Boston (2010). doi: 10.1007/978-1-4419-7314-6 CrossRefzbMATHGoogle Scholar
  9. 9.
    Schriber, T.J.: Introduction to Simulation. Wiley, New York (1991)Google Scholar
  10. 10.
    Yakimov, I.M., Kirpichnikov, A.P., Mokshin, V.V., Alyautdinova, G.R., Paigina, L.R.: Simulation modeling of business processes in Bizagi Modeler. Bull. Kazan Technol. Univ. 18(9), 236–239 (2015). Kazan. (in Russian)Google Scholar
  11. 11.
    Basic elements of queuering theory. Application to the Modelling of Computer Systems, France (2015)Google Scholar
  12. 12.
    Guerreiro, S., Vasconcelos, A., Tribolet, J.: Enterprise dynamic systems control enforcement of run-time business transactions. In: Albani, A., Aveiro, D., Barjis, J. (eds.) EEWC 2012. LNBIP, vol. 110, pp. 46–60. Springer, Heidelberg (2012). doi: 10.1007/978-3-642-29903-2_4 CrossRefGoogle Scholar
  13. 13.
    Zabawa, J., Radosiński, E.: Comparison of discrete rate modeling and discrete event simulation. methodological and performance aspects. In: Świątek, J., Wilimowska, Z., Borzemski, L., Grzech, A. (eds.) Information Systems Architecture and Technology. AISC, vol. 523, pp. 153–164. Springer, Cham (2017). doi: 10.1007/978-3-319-46589-0_12 Google Scholar
  14. 14.
    Gross, D., Harris, C.M.: Fundamentals of Queueing Theory, 2nd edn. Wiley, New York (1985)zbMATHGoogle Scholar
  15. 15.
    Garrido, J.M.: Introduction to flexsim. In: Garrido, J.M. (ed.) Object Oriented Simulation. Springer, Boston (2009). doi: 10.1007/978-1-4419-0516-1_3 CrossRefGoogle Scholar
  16. 16.
    Devyatkov, V.V.: Exceeded Editor of GPSS World: Main Possibilities. Print-Service Publ., Moscow (2013). (in Russian)Google Scholar
  17. 17.
    Bangsow, S.: Manufacturing Simulation with Plant Simulation and Simtalk. Springer, Heidelberg (2010). doi: 10.1007/978-3-642-05074-9 CrossRefGoogle Scholar
  18. 18.
    ProModel’s Portfolio Simulation Solution. http://www.promodel.com
  19. 19.
    Tarasov, S.V.: Application experience of component modeling in Transas GroupS training system development for cargo-ballast and technological operations. Autom. Remote Control 77(6), 1106–1114 (2016)MathSciNetCrossRefGoogle Scholar
  20. 20.
    Masmoudi, M., Leclaire, P., Cheutet, V., Casalino, E.: Modelling and simulation of the doctors’ availability in emergency department with SIMIO software. Case of study: Bichat-Claude Bernard hospital. In: Abbes, M.S., Choley, J.-Y., Chaari, F., Jarraya, A., Haddar, M. (eds.) Mechatronic Systems: Theory and Applications. LNME, pp. 119–129. Springer, Cham (2014). doi: 10.1007/978-3-319-07170-1_12 Google Scholar
  21. 21.
    Concannon, K., et al.: Simulation Modeling with SIMUL8, USA (2007)Google Scholar
  22. 22.
    Chakravarthy, S., Alfa, A.S.: A finite capacity queue with Markovian arrivals and two servers with group services. J. Appl. Math. Stoch. Anal. 7, 161–178 (1994)MathSciNetCrossRefzbMATHGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Igor Yakimov
    • 1
  • Alexander Kirpichnikov
    • 2
  • Vladimir Mokshin
    • 1
    • 3
    Email author
  • Zuhra Yakhina
    • 1
  • Rustem Gainullin
    • 2
  1. 1.Kazan National Research Technical University named after A. N. Tupolev KAIKazanRussian Federation
  2. 2.Kazan National Research Technological UniversityKazanRussian Federation
  3. 3.Automation and Control System LaboratorySiemens Engineering CenterKazanRussian Federation

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