1. Proceedings
  2. I3M
  3. 2019
  4. EMSS
  5. 10.46354/i3m.2019.emss.029

A ranking of the most known freeware and open source discrete-event simulation tools

  • a António A.C. Vieira  ,
  • b Luís M.S. Dias  ,
  • c Maribel Y. Santos  ,
  • d Guilherme A.B. Pereira  ,
  • e José A. Oliveira  
  • a,b,c,d,e ALGORITMI Research Centre, University of Minho, Portugal
Cite as
Vieira A.A.C., Dias L.M.S., Santos M.Y., Pereira G.A.B., Oliveira J.A. (2019). A ranking of the most known freeware and open source discrete-event simulation tools. Proceedings of the 31st European Modeling & Simulation Symposium (EMSS 2019), pp. 200-209. DOI: https://doi.org/10.46354/i3m.2019.emss.029.

Abstract

Freeware and open source simulation software can be of great relevant when applying simulation in companies that do not possess the required monetary resources to invest in traditional commercial software, since these can be unaffordable Even so, there is a lack of papers that contribute to literature with a comparison of opensource and freeware simulation tools. Furthermore, such existing papers fail to establish a proper assessment of these type of tools. In this regard, this paper proposes a study in which several freeware and open source discrete-event general purpose simulation tools were selected and compared, in order to propose a ranking based on the tools’ popularity, considering several criteria. For this purpose, 30 criteria were used to assess the score of each tool, leading to a podium composed by SimPy, JSim and JaamSim. Further conclusion and future work are discussed in the last section.

References

  1. Abu-Taieh, E M O, and A A R El Sheikh. 2007. “Commercial Simulation Packages: A Comparative Study.” International Journal of Simulation: Systems, Science and Technology 8 (2): 66–76.
  2. Byrne, N, P Liston, J Geraghty, and P Young. 2012. “The Potential Role of Open Source Discrete Event Simulation Software in the Manufacturing Sector.” In , 117–26.
  3. Dagkakis, G, and C Heavey. 2016. “A Review of Open Source Discrete Event Simulation Software for Operations Research.” Journal of Simulation 10 (3): 193–206. https://doi.org/10.1057/jos.2015.9.
  4. Dias, L., G. Pereira, and G. Rodrigues. 2007. “A Shortlist of the Most Popular Discrete Simulation Tools.” In Simulation News Europe, 17,33-36.
  5. Dias, L., G. Pereira, P. Vik, and J. Oliveira. 2011. “Discrete Simulation Tools Ranking: A Commercial Software Packages Comparison Based on Popularity.” In Industrial Simulation Conference. Venice, Italy, 6–8.
  6. Dias, Luis M. S., Antonio A. C. Vieira, Guilherme A. B. Pereira, and Jose A. Oliveira. 2016. “Discrete Simulation Software Ranking — A Top List of the Worldwide Most Popular and Used Tools.” In 2016 Winter Simulation Conference (WSC), 1060–71. IEEE. https://doi.org/10.1109/WSC.2016.7822165.
  7. Eurosis. 2019. “Simulation and Gaming Software Development Tools and Languages.” https://www.eurosis.org/cms/?q=node/61.
  8. Fowler, J W, and O Rose. 2004. “Grand Challenges in Modeling and Simulation of Complex Manufacturing Systems.” Simulation 80 (9): 469–76. https://doi.org/10.1177/0037549704044324.
  9. Google 2019. 2019. https://www.google.com.
  10. Hlupic, V, and R J Paul. 1999. “Guidelines for Selection of Manufacturing Simulation Software.” IIE Transactions 31 (1): 21–29. https://doi.org/10.1023/A:1007568516643.
  11. Hlupic, Vlatka. 2000. “Simulation Software: An Operational Research Society Survey of Academic and Industrial Users.” In Winter Simulation Conference Proceedings, 2:1676–83.
  12. Informs 2019. https://pubsonline.informs.org/magazine/ormstoday.
  13. Jadrić, Mario, Maja Ćukušić, and Antonia Bralić. 2014. “Comparison of Discrete Event Simulation Tools in an Academic Environment.” Croatian Operational Research Review 5 (2): 203–19. https://doi.org/10.17535/crorr.2014.0008.
  14. King, D. H., and Harvey S. Harrison. 2013. “Open-Source Simulation Software “JaamSim”” In 2013 Winter Simulations Conference (WSC), 2163–71. IEEE. https://doi.org/10.1109/WSC.2013.6721593.
  15. Klingstam, Pär, and Per Gullander. 1999. “Overview of Simulation Tools for Computer-Aided Production Engineering.” Computers in Industry 38 (2): 173–86. https://doi.org/10.1016/S0166-3615(98)00117-1.
  16. L’Ecuyer, P., and E. Buist. 2005. “Simulation in Java with SSJ.” In Proceedings of the Winter Simulation Conference, 2005., 611–20. IEEE. https://doi.org/10.1109/WSC.2005.1574301.
  17. L’Ecuyer, P L, Lakhdar Meliani, and Jean Vaucher. 2002. “SSJ: A Framework for Stochastic Simulation in Java.” In Simulation Conference, 2002. Proceedings of the Winter, 1:234–42. IEEE.
  18. Miller, John A, Andrew F Seila, and Xuewei Xiang. 2000. “The JSIM Web-Based Simulation Environment.” Future Generation Computer Systems 17 (2): 119–33. https://doi.org/10.1016/S0167-739X(99)00108-9.
  19. Page, Ernest H, Robert L Moose Jr., and Sean P Griffin. 1997. “Web-Based Simulation in Simjava Using Remote Method Invocation.” In , 468–74.
  20. Park, Hyeong-Tae, Jong-Geun Kwak, Gi-Nam Wang, and Sang C. Park. 2010. “Plant Model Generation for PLC Simulation.” International Journal of Production Research 48 (5): 1517–29. https://doi.org/10.1080/00207540802577961.
  21. Peixoto, Túlio Almeida, João José de Assis Rangel, Ítalo de Oliveira Matias, Fábio Freitas da Silva, and Eder Reis Tavares. 2017. “Ururau: A Free and Open-Source Discrete Event Simulation Software.” Journal of Simulation 11 (4): 303–21. https://doi.org/10.1057/s41273-016-0038-5.
  22. Sawhney, Anil, Hemant Deshpande, and Andre Mund. 2000. “JavaBeans-Based Framework for Construction Simulation.” In , 2:1919–25.
  23. Sawhney, Anil, Jayachandran Manickam, Andre Mund, and Jennifer Marble. 1999. “Java-Based Simulation of Construction Processes Using Silk.” In , 2:985–91.
  24. Sawhney, Anil, and Andre Mund. 1998. “Simulation Based Construction Management Learning System.” In , 2:1319–24.
  25. Vieira, A., L.S. Dias, G.A.B. Pereira, J.A. Oliveira, M.S. Carvalho, and P. Martins. 2015. “Using Simio to Automatically Create 3d Warehouses and Compare Different Storage Strategies.” FME Transactions 43 (4). https://doi.org/10.5937/fmet1504335V.
  26. Vieira, A., L.S. Dias, G.B. Pereira, and J.A. Oliveira. 2014. Micro Simulation to Evaluate the Impact of Introducing Pre-Signals in Traffic Intersections. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 8584 LNCS. https://doi.org/10.1007/978-3-319-09153-2_54.
  27. Vieira, A., L.S. Dias, G.B. Pereira, J.A. Oliveira, M.S. Carvalho, and P. Martins. 2016. “Automatic Simulation Models Generation of Warehouses with Milk Runs and Pickers.” In 28th European Modeling and Simulation Symposium, EMSS 2016. Winner of the Best Paper Award, 231–41.
  28. Vieira, A.A.C., L.M.S. Dias, G.A.B. Pereira, and J.A. Oliveira. 2017. Agent-Based Simulation to Assess the Performance of Intersections with Pre-Signals: Comparison with Roundabouts. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 10572 LNCS. https://doi.org/10.1007/978-3-319-68496-3_36.
  29. Vieira, A A C, L M S Dias, G A B Pereira, J A Oliveira, M Do Sameiro Carvalho, and P Martins. 2018. “Simulation Model Generation for Warehouse Management: Case Study to Test Different Storage Strategies.” International Journal of Simulation and Process Modelling 13 (4): 324–36. https://doi.org/10.1504/IJSPM.2018.093761.
  30. Vieira, António, Luís M. S. Dias, Guilherme Pereira, and José A. Oliveira. 2014. “Comparison of SIMIO and ARENA Simulation Tools.” In 12th Annual Industrial Simulation Conference (ISC2014), 5–13.
  31. Weatherly, R M, and E H Page. 2004. “Efficient Process Interaction Simulation in Java: Implementing Co-Routines within a Single Java Thread.” In , 2:1437–43.
  32. “Wikipedia.” 2019. https://en.wikipedia.org/wiki/List_of_discrete_event_simulation_software.