The last few years have seen an increase in the number of scholarly articles regarding JaamSim. One article in particular caught our eye. In its review of open source simulation software for production and logistics, Lang et al. (2021) concluded that:
"JaamSim provides everything which is necessary to model typical planning tasks in production and logistics and proves as a real alternative to commercial discrete-event simulation tools."
Of course, this observation was not news to us, but it was nice to see it recognized independently!
In an earlier article that reviewed a large number of open source simulation packages, Dagkakis and Heavey (2015) noted that:
"Out of all the OS DES projects we reviewed, JaamSim is the one with the most impressive 3d user interface that can compete against COTS [commercial off the shelf] DES software."
"The fact that a non-expert user can just download and test the software in a few minutes is something that is a scarce attribute in OS projects and especially in the DES domain."
"It is the only tool we found that is clearly industry driven."
These two articles and many more that are relevant to JaamSim are listed below:
Duin, H.; Neu, W.; Schüning, T.; Eschment, L.; Nobel, T.; Wurst, S. (2023): The planning of hyperloop-based cargo tubes routes for sustainable logistic solutions, ICPLT 2023: Advances in Resilient and Sustainable Transport, 306-320, doi: 10.1007/978-3-031-28236-2_19
Ruane, P.; Walsh, P.; Cosgrove, J. (2022): Development of a digital model and metamodel to improve the performance of an automated manufacturing line, Journal of Manufacturing Systems, Vol. 65, 538-549, doi: 10.1016/j.jmsy.2022.10.011
Kristiansen, O. S., Sandberg, U., Hansen, C., Jensen, M. S., Friederich, J., & Lazarova-Molnar, S. (2022). Experimental Comparison of Open Source Discrete-Event Simulation Frameworks. In D. Jiang, & H. Song (Eds.), Simulation Tools and Techniques: 13th EAI International Conference, SIMUtools 2021, Virtual Event, November 5-6, 2021, Proceedings (pp. 315-330). Springer. doi: 10.1007/978-3-030-97124-3_24
Lang, S.; Reggelin, T.; Müller, M.; Nahhas, A. (2021): Open-source discrete-event simulation software for applications in production and logistics: An alternative to commercial tools?, Procedia Computer Science, Vol. 180, 978-987, doi:10.1016/j.procs.2021.01.349
Kumar, A.; Krishnamurthi, R.; Nayyar, A.; Luhach, A. K.; Khan, M. S.; Singh, A. (2021): A novel software-defined drone network (SDDN)-based collision avoidance strategies for on-road traffic monitoring and management, Vehicular Communications, Vol. 28, doi:10.1016/j.vehcom.2020.100313
Kumar, A.; Krishnamurthi, R.; Nayyar, A.; Sharma, K.; Grover, V.; Hossain, E. (2020): A novel smart healthcare design, simulation, and implementation using healthcare 4.0 processes, IEEE Access, Vol. 8, 118433-118471, doi:10.1109/ACCESS.2020.3004790
Possik, J.; Zouggar-Amrani, A.; Vallespir, B.; Zacharewicz, G. (2021): Lean techniques impact evaluation methodology based on a co-simulation framework for manufacturing systems, International Journal of Computer Integrated Manufacturing, doi:10.1080/0951192X.2021.1972468
Gorecki, S.; Possik, J.; Zacharewicz, G.; Ducq, Y.; Perry, N. (2021): Business models for distributed-simulation orchestration and risk management, Information, Vol. 12, No. 71, doi:10.3390/info12020071
Ochs, J.; Biermann, F.; Piotrowski, T.; Erkens, F.; Nießing, B.; Herbst, L.; König, N.; Schmitt, R.H. (2021): Fully automated cultivation of adipose-derived stem cells in the StemCellDiscovery—a robotic laboratory for small-scale, high-throughput cell production including deep learning-based confluence estimation, Processes, Vol. 9, 575, doi:10.3390/pr9040575
Ochs, J.; Biermann, F.; Piotrowski, T.; Erkens, F.; Nießing, B.; Herbst, L.; König, N.; Schmitt, R.H. (2021): Fully automated cultivation of adipose-derived stem cells in the StemCellDiscovery—a robotic laboratory for small-scale, high-throughput cell production including deep learning-based confluence estimation, Processes, Vol. 9, 575, doi:10.3390/pr9040575
Amarantou,V.; Chatzoudes, D.; Angelidis, V.; Xanthopoulos, A.; Chatzoglou, P. (2021): Improving the operations of an emergency department (ED) using a combined approach of simulation and analytical hierarchical process (AHP), Journal of Simulation, doi:10.1080/17477778.2021.1981784
Xanthopoulos, A. S.; Koulouriotis, D. E. (2021): A comparative study of different pull control strategies in multi-product manufacturing systems using discrete event simulation, Advances in Production Engineering & Management, Vol. 16, No. 4, 473-484, doi:10.14743/apem2021.4.414
Xanthopoulos, A. S.; Koulouriotis, D. E. (2021): A comparative study of different pull control strategies in multi-product manufacturing systems using discrete event simulation, Advances in Production Engineering & Management, Vol. 16, No. 4, 473-484, doi:10.14743/apem2021.4.414
Kumar, A.; Sharma, K.; Singh, H.; Naugriya, S. G. ; Gill, S. S.; Buyya, R. (2021): A drone-based networked system and methods for combating coronavirus disease (COVID-19) pandemic, Future Generation Computer Systems, Vol. 115, 1-19, doi:10.1016/j.future.2020.08.046
Izquierdo, F.; Garcia, E.; Cortez, B.; Escobar, L. (2021): Flexible manufacturing systems optimization with meta-heuristic algorithm using open source software, Recent Advances in Electrical Engineering, Electronics and Energy, Vol. 763, doi:10.1007/978-3-030-72212-8_18
Larsson, R. (2021), Development and application of a tool for assessing the impact of failure modes on performance of underground drill rigs, Dissertation, Örebro University, Sweden
Gorecki, S.; Possik, J.; Zacharewicz, G.; Ducq, Y.; and Perry, N. (2020): A multicomponent distributed framework for smart production system modeling and simulation, Sustainability, Vol. 12, No. 17, 6969; doi:10.3390/su12176969
Kumar, A.; Srikanth, P.; Nayyar, A.; Sharma, G.; Pulipeti, S.; Krishnamurthi, R.; Alazab, M. (2020): A novel simulated-annealing based electric bus system design, simulation, and analysis for Dehradun smart city, IEEE Access, doi:10.1109/ACCESS.2020.2990190
Gorecki, S.; Possik, J.; Zacharewicz, G.; Ducq, Y.; and Perry, N. (2020): A multicomponent distributed framework for smart production system modeling and simulation, Sustainability, Vol. 12, No. 17, 6969; doi:10.3390/su12176969
Kumar, A.; Srikanth, P.; Nayyar, A.; Sharma, G.; Pulipeti, S.; Krishnamurthi, R.; Alazab, M. (2020): A novel simulated-annealing based electric bus system design, simulation, and analysis for Dehradun smart city, IEEE Access, doi:10.1109/ACCESS.2020.2990190
Kumar, A.; Sharma, D. K.; Nayyar, A.; Singh, S.; Yoon, B. (2020): Lightweight proof of game (LPoG): a proof of work (PoW)’s extended lightweight consensus algorithm for wearable kidneys, Sensors, Vol. 20, 2868, doi:10.3390/s20102868
Kim, S.; Chepenik, L. G. (2020): Use of computer modeling to streamline care in a psychiatric emergency room: a case report, Psychiatric Services, Vol. 71, 92–95, doi:10.1176/appi.ps.201900040
Kloock-Schreiber, D.; Siqueira, R.; Gembarski, P. C.; Lachmayer, R. (2020): Discrete-event simulation for specification design of products in product-service systems, Proceedings of the Design Society: DESIGN Conference, Vol. 1, 255-264, doi:10.1017/dsd.2020.295
Kiss, T.; DesLauriers, J.; Gesmier, G.; Terstyanszky, G.; Pierantoni, G.; Abu Oun, O.; Taylor, S. J. E.; Anagnostou, A.; Kovacs, J.; (2019): A cloud-agnostic queuing system to support the implementation of deadline-based application execution policies, Future Generation Computer Systems, Vol. 101, 99-111, doi:10.1016/j.future.2019.05.062
Zeng, W.; Baafi, E.; Walker, D. (2019): A simulation model to study bunching effect of a truck-shovel system, International Journal of Mining, Reclamation and Environment, Vol. 33, No. 2, 102-117, doi:10.1080/17480930.2017.1348284
Katsios, D.; Xanthopoulos, A. S.; Koulouriotis, D. E.; Kiatipis, A. (2018): A simulation optimisation tool and its production/inventory control application, International Journal of Simulation Modelling, Vol. 17, No. 2, 257-270, doi:10.2507/IJSIMM17(2)425
Ghafghazi, S.; Lochhead, K.; Mathey, A.; Forsell, N.; Leduc, S.; Mabee, W.; Gary Bull, G. (2017) Estimating mill residue surplus in Canada: a spatial forest fiber cascade modeling approach, Forest Products Journal, vol. 67, 205, doi:10.13073/FPJ-D-16-00031
Li, X.; Li, Z.; Wu, G. (2017): Lean precast production system based on the CONWIP method, KSCE Journal of Civil Engineering, doi:10.1007/s12205-017-2009-4
Kiss, T.; DesLauriers, J.; Gesmier, G.; Terstyanszky, G.; Pierantoni, G.; Abu Oun, O.; Taylor, S. J. E.; Anagnostou, A.; Kovacs, J.; (2019): A cloud-agnostic queuing system to support the implementation of deadline-based application execution policies, Future Generation Computer Systems, Vol. 101, 99-111, doi:10.1016/j.future.2019.05.062
Zeng, W.; Baafi, E.; Walker, D. (2019): A simulation model to study bunching effect of a truck-shovel system, International Journal of Mining, Reclamation and Environment, Vol. 33, No. 2, 102-117, doi:10.1080/17480930.2017.1348284
Katsios, D.; Xanthopoulos, A. S.; Koulouriotis, D. E.; Kiatipis, A. (2018): A simulation optimisation tool and its production/inventory control application, International Journal of Simulation Modelling, Vol. 17, No. 2, 257-270, doi:10.2507/IJSIMM17(2)425
Ghafghazi, S.; Lochhead, K.; Mathey, A.; Forsell, N.; Leduc, S.; Mabee, W.; Gary Bull, G. (2017) Estimating mill residue surplus in Canada: a spatial forest fiber cascade modeling approach, Forest Products Journal, vol. 67, 205, doi:10.13073/FPJ-D-16-00031
Li, X.; Li, Z.; Wu, G. (2017): Lean precast production system based on the CONWIP method, KSCE Journal of Civil Engineering, doi:10.1007/s12205-017-2009-4
Abas, Z. A.; Ee-Theng, L.; Rahman, A. F. N. A.; Abidin, Z. Z.; Shibghatullah, A. S. (2015): Enhanced scheduling traffic light model using discrete event simulation for improved signal timing analysis, ARPN Journal of Engineering and Applied Sciences, Vol. 10, No. 18
Dagkakis, G.; Heavey, C. (2015): A review of open source discrete event simulation software for operations research, Journal of Simulation, Vol. 10, No. 3, doi:10.1057/jos.2015.9
Sterling, T.; Kogler, D.; Anderson, M.; Brodowicz, M. (2014): SLOWER: A performance model for Exascale computing, Supercomputing Frontiers and Innovations, Vol. 1, No. 2, 42-57, doi:10.14529/jsfi140203
King, D. H.; Harrison, H. S.; Chudleigh, M. (2014): “JaamSim” described in three simple examples, Proceedings of the Operational Research Society Simulation Workshop 2014 (SW14)
King, D. H.; Harrison, H. S. (2013). JaamSim open-source simulation software, Proceedings of the 2013 Grand Challenges on Modeling and Simulation Conference, doi:10.5555/2557668.2557669
King, D. H.; Harrison, H. S. (2013): Open-source simulation software “JaamSim”, 2013 Winter Simulations Conference (WSC), 2163-2171, doi:10.1109/WSC.2013.6721593
Dagkakis, G.; Heavey, C. (2015): A review of open source discrete event simulation software for operations research, Journal of Simulation, Vol. 10, No. 3, doi:10.1057/jos.2015.9
Sterling, T.; Kogler, D.; Anderson, M.; Brodowicz, M. (2014): SLOWER: A performance model for Exascale computing, Supercomputing Frontiers and Innovations, Vol. 1, No. 2, 42-57, doi:10.14529/jsfi140203
King, D. H.; Harrison, H. S.; Chudleigh, M. (2014): “JaamSim” described in three simple examples, Proceedings of the Operational Research Society Simulation Workshop 2014 (SW14)
King, D. H.; Harrison, H. S. (2013). JaamSim open-source simulation software, Proceedings of the 2013 Grand Challenges on Modeling and Simulation Conference, doi:10.5555/2557668.2557669
King, D. H.; Harrison, H. S. (2013): Open-source simulation software “JaamSim”, 2013 Winter Simulations Conference (WSC), 2163-2171, doi:10.1109/WSC.2013.6721593