Simulation model of supply networks development

  • Petr Fiala  , 
  • b Martina Kuncová  
  • ab College of Polytechnics Jihlava, Czech Republic

Cite as
Fiala P., Kuncová M. (2019). Simulation model of supply networks development. Proceedings of the 18th International Conference on Modelling and Applied Simulation (MAS 2019), pp. 16-21. DOI: https://doi.org/10.46354/i3m.2019.mas.003
 Download PDF

Abstract

The paper is dedicated to network development in the network economy. The current economy needs to look not only at networks with only dynamic flows and with a fixed structure, but as a dynamic system its structure evolves and changes. Structure and behaviour dynamics of network systems can be modelled as complex adaptive systems and use agent-oriented simulation to demonstrate origin, perturbation effects, and sensitivity with regard to initial conditions. Survival of firms is associated with the value of so-called fitness function. Firms whose fitness value falls below a certain threshold will be extinguished. In this way, it is possible to partially model network growth. A simulation model in SIMUL8 is proposed.

References

  1. Concannon, K., et al., 2007. Simulation Modeling with SIMUL8. Canada:Visual Thinking International.
  2. Fiala P., 2009. Dynamic supply networks (in Czech). Praha: Professional Publishing.
  3. Fiala P., 2016. Dynamic pricing and resource allocation in networks (in Czech). Praha: Professional Publishing.
  4. Ficova, P. and Kuncova, M., 2013. Looking for the equilibrium of the shields production system via simulation model. Proceedings of the Conference Modeling and Applied Simulation (MAS), pp. 50-56. September 25-27, Athens (Greece).
  5. Fousek, J., Kuncova, M. and Fabry, J., 2017. Discrete event simulation – production model in SIMUL8. Proceedings of the European Conference on Modelling and Simulation (ECMS), pp. 229–234, May 23-26, Budapest (Hungary).
  6. Greasley, A., 2003. Simulation modelling for business. Innovative Business Textbooks. London: Ashgate.
  7. Kuncova, M., Skalova, M., 2018. Discrete Event Simulation Applied to the Analysis of the Cashdesk Utilization in a Selected Shop of the Retail Chain. Proceedings of the Conference Modeling and Applied Simulation (MAS), pp. 76–82, September 17-19, Budapest (Hungary).
  8. Omogbai, O. and Salonitis, K. 2016. Manufacturing system lean improvement design using discrete event simulation. Procedia CIRP – Conference on Manufacturing Systems 57, pp. 195 – 200.
  9. Pathak S., Dilts D.M., 2004. CAS-SIM: Complex Adaptive Supply Network Simulator, A Scenario Analysis Tool For Analyzing Supply Networks. Proceedings of Production and Operations Management Society Conference, Cancun.
  10. Pathak S., Dilts D.M., Biswas G., 2003. A Hybrid Simulator for Simulating Complex Adaptive
    Supply Chain Networks. Proceedings of Winter Simulation Conference, New Orleans.
  11. Utterback J. (1994). Mastering the Dynamics of Innovation. Boston: HBS Press.
  12. Utterback J., Suarez F., 1993. Innovation: Competition and Industry Structure. Research Policy 15, 285-305.