Introducing JaamSim Pro

JaamSim Software Inc. is pleased to announce a new commercial software product 'JaamSim Pro' that extends the open-source JaamSim by adding libraries of objects for vehicle motion and material flow. It is targeted at the mining and oil & gas industries and the consultants that build models for these companies. These complex models include everything from the production and processing of one or more materials through various transportation modes and storage locations through to the end user. They often have hundred or even thousands of active components.

The following model prepared by Hypercube Scientific (hypercubescientific.com.au) is a good example of an end-to-end model for a hypothetical mining company:

What makes JaamSim Pro special is that these models can be constructed in much less time and that they execute many times faster than the models built with other software. For example, the model shown above executes one year of simulated time in about 30 minutes on a typical computer. With other software a simulation run can require 2 or more hours of execution time.

JaamSim Pro executes so much faster than other simulation software because it simulates material flow and vehicle motion using next-event logic instead of the fixed time steps used by other software. Next-event logic is more difficult for our programmers to implement, but the increase in execution speed is enormous. It also avoids the problems of accumulated round-off error and makes it unnecessary for the model builder to choose the size of the time steps.

The JaamSim Pro website (jaamsimpro.com) provides a series of videos that show the types of models that can be constructed.

Lastly, please note that the free open source JaamSim can still be used for both academic and commercial purposes. Its Apache 2.0 license is one of the most permissive licenses for open source software. JaamSim Pro is only required if its libraries of material flow and vehicle motion objects are needed for a model. Any new features that are not related to these two libraries will be included in the open source JaamSim.

Articles on JaamSim

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

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

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

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

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

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

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

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

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

King, D. H.; Harrison, H. S. (2010): Discrete-event simulation in Java: a practitioner's experience, Proceedings of the 2010 Conference on Grand Challenges in Modeling & Simulation (GCMS '10), Society for Modeling & Simulation International, 436 – 441, doi:10.5555/2020619.2020678

Teaching Simulation using JaamSim

Over the years we have tried to keep track of all the universities and colleges that use JaamSim for their courses in discrete event simulation. Typically, we ask the instructor to provide details about the course in the form of a post to the JaamSim forum under the topic "Teaching Simulation using JaamSim" (link). Some instructors have generously shared their course notes to make it easier for others to use JaamSim in their courses.

Included in the post are the following institutions:

• Rutgers University, USA
• The Wharton School, University of Pennsylvania, USA
• United States Naval Academy, USA
• Karlstad University, Sweden
• University of Zaragoza, Spain
• Swiss Distance University of Applied Sciences, Switzerland
• Maastricht University, The Netherlands
• University of Antwerp, Belgium
• Albstadt-Sigmaringen University, Germany
• Derby College, UK
• Conestoga College, Canada
• Capilano University, Canada
• University of Auckland, New Zealand
• Universidad del Valle de Guatemala, Guatemala
• Universidad de San Carlos de Guatemala, Guatemala
• Universidad EAFIT, Colombia
• Universidade Tecnológica Federal do Paraná, Brazil
• Universidade Federal de Ouro Preto, Brazil
• Universidade Federal Rural do Semi-Árido, Brazil
• Universidade Federal de São João del-Rei, Brazil

More information about these courses and names of the instructors can be found by clicking on the link to the forum post given above or by searching for this topic in the JaamSim forum.

With 12,000 downloads of the software per year, we expect that JaamSim is being used at many more institutions than the ones listed above. If you would like to add your university or college to this list, please post the requested information about your course under this topic in the JaamSim forum.