References
- Alomari I., Al-Samarraie H., Yousef R., The Role of Gamification Techniques in Promoting Student Learning: A Review and Synthesis, Journal of Information Technology Education: Research, 18, pp. 395-417 (2019), Available at: https://doi.org/10.28945/4417.
- Bangsow S., Tecnomatix Plant Simulation: Modeling and Programming by Means of Examples, Cham: Springer International Publishing (2020), Available at: https://doi.org/10.1007/978-3-030-41544-0.
- Baumann-Birkbeck L. et al., Can a virtual microbiology simulation be as effective as the traditional Wetlab for pharmacy student education?, BMC Medical Education, 21(1), p. 583 (2021), Available at: https://doi.org/10.1186/s12909-021-03000-3.
- Brailsford S.C. et al., An Analysis of the Academic Literature on Simulation and Modeling in Health Care, in N. Mustafee (Ed.) Operational Research for Emergency Planning in Healthcare: Volume 2. London: Palgrave Macmillan UK, pp. 231-251 (2016), Available at: https://doi.org/10.1007/978-1-137-57328-5_11.
- Breznik M., Buchmeister B., Vujica Herzog N., Assembly Line Optimization Using MTM Time Standard and Simulation Modeling‒A Case Study, Applied Sciences, 13(10), p. 6265 (2023), Available at: https://doi.org/10.3390/app13106265.
- Carter J.L., Coletti R.J., Harris R.P., Quantifying and monitoring overdiagnosis in cancer screening: a systematic review of methods, BMJ, 350, p. 18 (2015), Available at: https://doi.org/10.1136/bmj.g7773.
- Chen T., Chiu M.-C., Development of a cloud-based factory simulation system for enabling ubiquitous factory simulation, Robotics and Computer-Integrated Manufacturing, 45, pp. 133-143 (2017), Available at: https://doi.org/10.1016/j.rcim.2015.12.010.
- Ďuriška M. et al., Use of a Software Application to Generate a Sequence for Simulation Model Creation, Applied Sciences, 13(9), p. 5433 (2023), Available at: https://doi.org/10.3390/app13095433.
- Fabbri A., Simulation of regional logistics systems with agent-based modelling: a Dubai case study, Politecnico di Torino (2020), Available at: https://webthesis.biblio.polito.it/14700/ (Accessed: 21 March 2025).
- Fedorko G. et al., Research on Using the Tecnomatix Plant Simulation for Simulation and Visualization of Traffic Processes at the Traffic Node, Applied Sciences, 12(23), p. 12131 (2022), Available at: https://doi.org/10.3390/app122312131.
- Goldsman D., Nance R., Wilson J., A brief history of simulation revisited, in Proceedings - Winter Simulation Conference, pp. 567-574 (2010), Available at: https://doi.org/10.1109/WSC.2010.5679129.
- Guseva E. et al., Discrete event simulation modelling of patient service management with Arena, Journal of Physics: Conference Series, 1015(3), p. 032095 (2018), Available at: https://doi.org/10.1088/1742-6596/1015/3/032095.
- Habibifar N. et al., Performance optimisation of a pharmaceutical production line by integrated simulation and data envelopment analysis, International Journal of Simulation and Process Modelling, 14, p. 360 (2019), Available at: https://doi.org/10.1504/IJSPM.2019.103587.
- Hofmann W., Branding F., Implementation of an IoT- and Cloud-based Digital Twin for Real-Time Decision Support in Port Operations, IFAC-PapersOnLine, 52(13), pp. 2104-2109 (2019), Available at: https://doi.org/10.1016/j.ifacol.2019.11.516.
- Hovanec M. et al., Simulating a Digital Factory and Improving Production Efficiency by Using Virtual Reality Technology, Applied Sciences, 13(8), p. 5118 (2023), Available at: https://doi.org/10.3390/app13085118.
- Ivanov D., Operations and Supply Chain Simulation with AnyLogic, 2nd edition, Berlin: Berlin School of Economics and Law (2017), Available at: https://www.google.com/url?sa=t&source=web&rct=j&opi=89978449&url=https://www.anylogic.com/upload/pdf/Ivanov_AL_book_2017.pdf&ved=2ahUKEwizvtr6huGMAxXvcvEDHSqKC0cQFnoECBkQAQ&usg=AOvVaw0SXi6F Ed9EyK7IT3im8hbA.
- Ivanov D., Introduction to Supply Chain Analytics: With Examples in AnyLogic and anyLogistix Software, Cham: Springer Nature Switzerland (Classroom Companion: Business) (2024), Available at: https://doi.org/10.1007/978-3-031-51241-4.
- Kim H. et al., Modeling the future of tobacco control: Using SimSmoke to explore the feasibility of the tobacco endgame in Korea, Tobacco Induced Diseases, 21, p. 147 (2023), Available at: https://doi.org/10.18332/tid/174127.
- Kreft J.-U., Booth G., Wimpenny J.W.T., BacSim, a simulator for individual-based modelling of bacterial colony growth, Microbiology, 144(12), pp. 3275-3287 (1998), Available at: https://doi.org/10.1099/00221287-144-12-3275.
- Leal F. et al., A practical guide for operational validation of discrete simulation models, Pesquisa Operacional, 31, pp. 57-77 (2011), Available at: https://doi.org/10.1590/S0101-74382011000100005.
- Martins L.M. et al., Comparative study of autonomous production control methods using simulation, Simulation Modelling Practice and Theory, 104, p. 102142 (2020), Available at: https://doi.org/10.1016/j.simpat.2020.102142.
- Oliff H. et al., The Ethical Use of Human Data for Smart Manufacturing: An Analysis and Discussion, Procedia CIRP, 93, pp. 1364-1369 (2020), Available at: https://doi.org/10.1016/j.procir.2020.06.001.
- Pires M.C. et al., Simulation-Based Optimization for the Integrated Control of Production and Logistics: A Performance Comparison, IFAC-PapersOnLine, 53(2), pp. 10639-10644 (2020), Available at: https://doi.org/10.1016/j.ifacol.2020.12.2824.
- Reynolds M. et al., Using discrete event simulation to design a more efficient hospital pharmacy for outpatients, Health Care Management Science, 14(3), pp. 223-236 (2011), Available at: https://doi.org/10.1007/s10729-011-9151-1.
- Robinson S., Exploring the relationship between simulation model accuracy and complexity, Journal of the Operational Research Society, 74(9), pp. 1992-2011 (2023), Available at: https://doi.org/10.1080/01605682.2022.2122740.
- Siderska J., Application of Tecnomatix Plant Simulation for modeling production and logistics processes, Business, Management and Economics Engineering, 14(1), pp. 64-73 (2016), Available at: https://doi.org/10.3846/bme.2016.316.
- Stanković R., Božić, D., Applying Simulation Modelling in Quantifying Optimization Results, Tehnički glasnik, 15(4), pp. 518-523 (2021), Available at: https://doi.org/10.31803/tg-20210326111551.
- Vázquez-Serrano J., Peimbert-García R., Cárdenas-Barrón L., Discrete-Event Simulation Modeling in Healthcare: A Comprehensive Review, International Journal of Environmental Research and Public Health, 18, p. 12262 (2021), Available at: https://doi.org/10.3390/ijerph182212262.
- VDI 3633 Part 1, Simulation of Systems in Materials Handling, Logistics and Production: Fundamentals, Verein Deutscher Ingenieure (VDI) (2014), Available at: https://www.vdi.de/en/home/vdi-standards/details/vdi-3633-blatt-1-simulation-of-systems-in-materials-handling-logistics-and-production-fundamentals (Accessed: 27 March 2025).
- Zhang P. et al., Health Utility Scores for People with Type 2 Diabetes in U.S. Managed Care Health Plans, Diabetes Care, 35(11), pp. 2250-2256 (2012), Available at: https://doi.org/10.2337/dc11-2478.
- Zhang X., Application of discrete event simulation in health care: a systematic review, BMC Health Services Research, 18(1), p. 687 (2018), Available at: https://doi.org/10.1186/s12913-018-3456-4.
- Zhao J., Aghezzaf E.-H., Cottyn J., An extension of the Core Manufacturing Simulation Data standard to enhance the interoperability for discrete event simulation, Procedia CIRP, 130, pp. 1632-1637 (2024a), Available at: https://doi.org/10.1016/j.procir.2024.10.293.
- Zhao J., Aghezzaf E.-H., Cottyn J., Interoperability performance evaluation for discrete event simulation models: A step towards multi-level data exchange, Procedia CIRP, 128, pp. 72-77 (2024b), Available at: https://doi.org/10.1016/j.procir.2024.06.007.