References
- Abdulmalek, F. A., & Rajgopal, J. (2007). Analyzing the benefits of lean manufacturing and value stream mapping via simulation: A process sector case study. International Journal of Production Economics, 107(1), 223–236. https://doi.org/https://doi.org/10.1016/j.ijpe.2006.09.009
- Agyapong-Kodua, K., Weston, R. H., & Ratchev, S. (2012). The integrated use of enterprise and system dynamics modelling techniques in support of business decisions. Advances in Decision Sciences, 2012, 1–25. https://doi.org/https://doi.org/10.1155/2012/804324
- Agyapong-Kodua, K., & Weston, R. H. (2011). Systems approach to modelling cost and value dynamics in manufacturing enterprises. International Journal of Production Research, 49(8), 2143–2167. https://doi.org/https://doi.org/10.1080/00207540903436661
- Alrabghi, A., & Tiwari, A. (2015). State of the art in simulation-based optimisation for maintenance systems. Computers and Industrial Engineering, 82, 167–182. https://doi.org/https://doi.org/10.1016/j.cie.2014.12.022
- An, L., Jeng, -J.-J., Lee, Y. M., & Ren, C. (2007). Effective workforce lifecycle management via System Dynamics modeling and simulation. Winter Simulation Conference. Proceedings of Winter Simulation Conference (pp. 2187–2195). Washington.
- Atieh, A. M., Kaylani, H., Almuhtady, A., & Al-Tamimi, O. (2016). A value stream mapping and simulation hybrid approach: Application to glass industry. The International Journal of Advanced Manufacturing Technology, 84(5), 1573–1586. https://doi.org/https://doi.org/10.1007/s00170-015-7805-8
- Babashov, V., Aivas, I., Begen, M. A., Cao, J. Q., Rodrigues, G., D’Souza, D., Lock, M., & Zaric, G. S. (2017). Reducing patient waiting times for radiation therapy and improving the treatment planning process: A discrete-event simulation model (radiation treatment planning). Clinical Oncology, 29(6), 385–391. https://doi.org/https://doi.org/10.1016/j.clon.2017.01.039
- Banks, J. (1998). Handbook of simulation: Principles, methodology, advances, applications, and practice. John Wiley & Sons, Inc.
- Banks, J., Carson, J. S., Nelson, B. L., & Nicol, D. M. (2010). Discrete-event system simulation (5th ed.). Pearson Prentice Hall.
- Baril, C., Gascon, V., Miller, J., & Côté, N. (2016). Use of a discrete-event simulation in a Kaizen event: A case study in healthcare. European Journal of Operational Research, 249(1), 327–339. https://doi.org/https://doi.org/10.1016/j.ejor.2015.08.036
- Bem-Tovim, D., Filar, J., Hakendorf, P., Qin, S., Thompson, P., & Ward, D. (2016). Hospital event simulation model: Arrivals to discharge–design, development and application. Simulation Modelling Practice and Theory, 68, 80–94. https://doi.org/https://doi.org/10.1016/j.simpat.2016.07.004
- Bevilacqua, M., Ciarapica, F. E., Mazzuto, G., & Paciarotti, C. (2015). The impact of business growth in the operation activities: A case study of aircraft ground handling operations. Production Planning & Control: The Management of Operations, 26(7), 37–41. https://doi.org/https://doi.org/10.1080/09537287.2014.939234
- Biolchini, J. C. D. A., Mian, P. G., Natali, A. C. C., Conte, T. U., & Travassos, G. H. (2007). Scientific research ontology to support systematic review in software engineering. Advanced Engineering Informatics, 21(2), 133–151. https://doi.org/https://doi.org/10.1016/j.aei.2006.11.006
- Bisogno, S., Calabrese, A., Gastaldi, M., & Levialdi, N. (2016). Combining modelling and simulation approaches How to measure performance.Business Process Management Journal, 22(1), 56–74. https://doi.org/https://doi.org/10.1108/BPMJ-02-2015-0021
- Bublitz, A., Ringler, P., Genoese, M., & Fichtner, W. (2014). Agent-based simulation of the German and French wholesale electricity markets - Recent extensions of the powerACE model with exemplary applications. ICAART. Proceedings of the 6th International Conference on Agents and Artificial Intelligence (pp. 40–49). Angers, Loire Valley, France
- Bureš, V. (2015). Comparative analysis of system dynamics software packages. International Review on Modelling and Simulations, 8(2), 245–256. https://doi.org/https://doi.org/10.15866/iremos.v8i2.5401
- Caro, J. J. (2005). Pharmacoeconomic analyses using discrete event simulation. Pharmacoeconomics, 23(4), 323–332. https://doi.org/https://doi.org/10.2165/00019053-200523040-00003
- Cheng, T., Feng, C., & Hsu, M. (2006). An integrated modeling mechanism for optimizing the simulation model of the construction operation. Automation in Construction, 15(3), 327–340. https://doi.org/https://doi.org/10.1016/j.autcon.2005.06.016
- Choong, C. G., & McKay, A. (2014). Sustainability in the Malaysian palm oil industry. Journal of Cleaner Production, 85, 258–264. https://doi.org/https://doi.org/10.1016/j.jclepro.2013.12.009
- Chwif, L., & Montevechi, J. A. B. (2015). Are visually appealing simulation models preferable? Winter Simulation Conference (pp. 159–170). Huntington Beach, CA, USA.
- Clouth, J., Knoll, S., & Eichmann, F. (2010). Evaluating health care using system dynamics modelling – A case study in Schizophrenia. Gesundh Ökon and Qualitats Management, 15, 302–310. https://doi.org/http://doi.org/10.1055/s-0028-1109447
- Cook, D. J., Greengold, N. L., Ellrodt, A. G., & Weingarten, S. R. (1997). The relation between systematic reviews and practice guidelines. [review] [58 refs]. Annals of Internal Medicine, 127(3), 210–216. https://doi.org/https://doi.org/10.7326/0003-4819-127-3-199708010-00006
- Cournut, S., & Dedieu, B. (2004). A discrete events simulation of flock dynamics: A management application to three lambings in two years. Animal Research, 53(5), 383–403. https://doi.org/https://doi.org/10.1051/animres:2004025
- Da Silva, C. E. S., Salgado, E. G., Mello, C. H. P., Da Oliveira, E. S., & Leal, F. (2014). Integration of computer simulation in design for manufacturing and assembly. International Journal of Production Research, 52(10), 2851–2866. https://doi.org/https://doi.org/10.1080/00207543.2013.853887
- De Rangel, J. J. A., & Nunes, A. F. (2011). Use of IDEF-SIM to document simulation models. In: Winter Simulation Conference (pp. 2194–2205). Phoenix, AZ.
- Dengiz, B., & Belgin, O. (2014). Simulation optimization of a multi-stage multi-product paint shop line with response surface methodology. Simulation: Transactions Of The Society for Modeling and Simulation International, 90(3), 265–274. https://doi.org/https://doi.org/10.1177/0037549713516508
- Ding, X. J., & Sun, F. X. (2014). An overview of VV&A methods for conceptual model. Applied Mechanics and Materials, 444–445,860–864. https://doi.org/https://doi.org/10.4028/www.scientific.net/AMM.444-445.860
- Djanatliev, A., & German, R. (2013). Prospective healthcare decision-making by combined system dynamics, discrete-event and agent-based simulation. Winter Simulation Conference. Proceedings of Winter Simulation Conference (pp. 270–281). Washington.
- Dong, F., Liu, H., & Lu, B. (2012). Agent-based simulation model of single point inventory system. Systems Engineering Procedia, 4(2), 298–304. https://doi.org/https://doi.org/10.1016/j.sepro.2011.11.079
- Dundović, Č., Bilić, M., & Dvornik, J. (2009). Contribution to the development of a simulation model for a seaport in specific operating conditions. PROMET - Traffic&Transportation, 21(5), 331–340. https://doi.org/https://doi.org/10.7307/ptt.v21i5.248
- Edwards, P., Clarke, M., DiGuiseppi, C., Pratap, S., Roberts, I., & Wentz, R. (2002). Identification of randomized controlled trials in systematic reviews: Accuracy and reliability of screening records. Statistics in Medicine, 21(11), 1635–1640. https://doi.org/https://doi.org/10.1002/sim.1190
- Ekyalimpa, R., AbouRizk, S., Farrar, J. 2012 Effective strategies for simulatinf one-of-a-kind construction projects. Winter Simulation Conference. Proceedings of Winter Simulation Conference (pp. 1–13). Berlin.
- Elbanhawy, E. Y., Dalton, R., Shankar, V. N., & Warith, K. A. A. (2014). Hybrid-OD matrix based simulation approach to identify E-charging hotspots in transport network. IEEE Transportation Electrification Conference and Expo (ITEC) (pp. 1–6). Dearborn. https://doi.org/https://doi.org/10.1109/ITEC.2014.686178.
- Fayoumi, A., & Loucopoulos, P. (2016). Conceptual modeling for the design of intelligent and emergent information systems. Expert Systems with Applications, 59, 174–194. https://doi.org/https://doi.org/10.1016/j.eswa.2016.04.019
- Flood, I. (2015). Computing in Civil Engineering. 2015 International Workshop on Computing in Civil Engineering (pp. 692–699). Austin, Texas.
- Francisco, R. P., Campos, D. P., Frazzon, E. M., & Machado, R. L. (2016). On the application of modelling and simulation to compare human- and automation-based order-picking systems. IFAC-PapersOnLine, 49(12), 1062–1067. https://doi.org/https://doi.org/10.1016/j.ifacol.2016.07.583
- Fu-gui, D., Hui-mei, L., & Bing-de, L. (2012). Agent-based simulation model of single point inventory system. Systems Engineering Procedia, 4, 298–304. https://doi.org/https://doi.org/10.1016/j.sepro.2011.11.079
- Furian, N., O’Sullivan, M., Walker, C., Vössner, S., & Neubache, D. (2015). A conceptual modeling framework for discrete event simulation using hierarchical control structures. Simulation Modelling Practice and Theory, 56, 82–96. https://doi.org/https://doi.org/10.1016/j.simpat.2015.04.004
- Gagliardi, D., Niglia, F., & Battistella, C. (2014). Evaluation and design of innovation policies in the agro-food sector: An application of multilevel self-regulating agents. Technological Forecasting and Social Change, 85, 40–57. https://doi.org/https://doi.org/10.1016/j.techfore.2013.10.015
- Gaion, S., Fanti, M. P., Mininel, S., Ukovich, W., & Vatta, F. (2009). Modelling and validation of alarm management workflow in healthcare integrating IHE-PCD profile and coloured petri nets. IFAC Proceedings Volumes (IFAC-PapersOnline), 2(PART 1), 169–174. https://doi.org/https://doi.org/10.3182/20090610-3-IT-4004.00034
- Garani, G., & Adam, G. K. (2008). Qualitative modelling at the design of concrete manufacturing machinery. International Journal of Computers and Applications, 30(4), 325–330. https://doi.org/https://doi.org/10.1080/1206212X.2008.11441912
- Garousi, V., & Pfahl, D. (2016). When to automate software testing? A decision-support approach based on process simulation. Journal of Software: Evolution and Process, 28(4), 272–285. https://doi.org/https://doi.org/10.1002/smr.1758
- Geller, A., & Alam, S. J. (2010). A socio-political and -cultural model of the war in Afghanistan. International Studies Review, 12(1), 8–30. https://doi.org/https://doi.org/10.1111/j.1468-2486.2009.00910.x
- Harrell, C., Ghosh, B. K., & Bowden, R. (2012). Simulation using promodel (3th ed.). McGraw-Hill Education.
- Heeg, B., Buskens, E., Knapp, M., Van Aalst, G., Dries, P. J. T., de Haan, L., & Van Hout, B. A. (2005). Modelling the treated course of schizophrenia: Development of a discrete event simulation model. PharmacoEconomics, 23(Suppl 1), 17–33. https://doi.org/https://doi.org/10.2165/00019053-200523001-00003
- Hennemann, F. A., & Rabelo, R. J. (2006). A hybrid decision support system made up of Petri nets, simulation, and expert system. Controle y Automação, 17(1), 10–23. https://doi.org/https://doi.org/10.1590/S0103-17592006000100002
- Herpel, T., & German, R. (2009). A simulation approach for the design of safety-relevant automotive multi-ECU systems. System of Systems Engineering, IEEE International Conference on System of Systems Engineering (SoSE) (pp. 1–8). Albuquerque.
- Hou, S. (2013). Distribution center logistics optimization based on simulation. Research Journal of Applied Sciences, Engineering and Technology, 5(21), 5107–5111. https://doi.org/https://doi.org/10.19026/rjaset.5.4405
- Huirong, W., & Xiaoning, Z. (2010). Analysis on key factors of container seamless transportation operating based on system dynamics. 2010 International Conference on Computer Application and System Modeling (ICCASM) . 2010 International Conference on Computer Application and System Modeling (ICCASM) (pp. 379–382). Taiyuan, China.
- Jagathy Raj, V. P., & Acharya, D. (2009). Evaluation of a proposed hot metal distribution system for an integrated steel plant using simulation. International Journal of Operations and Quantitative Management, 15(4), 273–292.
- Jahangirian, M., Eldabi, T., Naseer, A., Stergioulas, L. K., & Young, T. (2010). Simulation in manufacturing and business: A review. European Journal of Operational Research, 203(1), 1–13. https://doi.org/https://doi.org/10.1016/j.ejor.2009.06.004
- Ju, F., Lee, H. K., Osarogiagbon, R. U., Yu, X., Faris, N., & Li, J. (2015). Computer Modeling of Lung Cancer Diagnosis-to-treatment Process. Translational Lung Cancer Research, 4(4), 404–414. https://doi.org/https://doi.org/10.3978/j.issn.2218-6751.2015.07.16.
- Karagöz, N. A., & Demirörs, O. (2011). Conceptual modeling notations and techniques. In S. Robinson, R. Brooks, K. Kotiadis, & D.-J. Van der Zee (Eds.), Conceptual modeling for discrete-event simulation (pp. 179–209). Taylor & Francis Group.
- Karnon, J. (2003). Alternative decision modelling techniques for the evaluation of health care technologies: Markov processes versus discrete event simulation. Health Economics, 12(10), 837–848. https://doi.org/https://doi.org/10.1002/hec.770
- Kashimbiri, N., Chen, Y.-F., & Zhou, J.-X. (2005). Risk communications: Around the world. Assessment of effects of human development on the environment by using system dynamic modeling technique (SD): A case study of the Mkomazi watershed (Pangani basin) in Northeastern Tanzania. Human and Ecological Risk Assessment, 11(2), 451–467. https://doi.org/https://doi.org/10.1080/10807030590925641
- Kitchenham, B., & Charters, S. (2007). Guidelines for performing systematic literature reviews in software engineering Version 2.3. Engineering, 45(4ve), 1051.
- Koivisto, M. (2017). Pitfalls in modeling and simulation. Procedia Computer Science, 119, 8–15. https://doi.org/https://doi.org/10.1016/j.procs.2017.11.154
- Kress, R., Cemerlic, A., Kress, J., Varghese, J.2010 Inverse discrete event modeling for facility parameter estimation. Winter Simulation Conference. Proceedings of Winter Simulation Conference (pp. 861–868). Baltimore.
- Krogstie, J., Lindland, O. I., & Sindre, G. (1995). Defining quality aspects for conceptual models. In E. D. Falkenberg, W. Hesse, & A. Olive (Eds.), Information system concepts: Towards a consolidation of views (pp. 216–231). Springer.
- Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33(1), 159. https://doi.org/https://doi.org/10.2307/2529310
- Li, S., Xu, W., & Liang, X. (2014). Dynamic model for paper mills facilities using template-based load modeling technique. 2014 IEEE/IAS. 50th Industrial & Commercial Power Systems Technical Conference (pp. 1–11). http://ieeexplore.ieee.org/document/6839158/
- Lin, C.-S., Yang, -C.-C., & Yeh, C.-H. (2015). Modeling and analysis of water resources system problems by using the causal feedback loop diagram of system dynamics. WSEAS transactions on environment and development. WSEAS transactions on environment and development (pp. 143–154).
- Lindland, O. I., Sindre, G., & Solvberg, A. (1994). Quality in conceptual modeling. IEEE Software, 11(2), 42–49. https://doi.org/https://doi.org/10.1109/52.268955
- Liraviasl, K. K., Elmaraghy, H., Hanafy, M., & Samy, S. N. (2015). A framework for modelling reconfigurable manufacturing systems using hybridized discrete-event and agent-based simulation. IFAC-PapersOnLine, 48(3), 1490–1495. https://doi.org/https://doi.org/10.1016/j.ifacol.2015.06.297
- Liu, J., Yu, Y., Zhang, L., & Nie, C. (2011). An Overview of Conceptual Model for Simulation and Its Validation. 2011 International Conference on Advances in Engineering. 2011 International Conference on Advances in Engineering (pp. 152–158). Nanjing.
- Macal, C., & North, M. (2014). Introductory tutorial: Agent-Based modeling and simulation. Winter Simulation Conference. Proceedings of Winter Simulation Conference. Savannah.
- Mahato, B. K., & Ogunlana, S. O. (2011). Conflict dynamics in a dam construction project: A case study. Built Environment Project and Asset Management, 1(2), 176–194. https://doi.org/https://doi.org/10.1108/20441241111180424
- Martinez-Olvera, C. (2007). Reference model of the manufacturing execution activity in make-to-order environments. International Journal of Production Research, 47(6), 1635–1659. https://doi.org/https://doi.org/10.1080/00207540701636330
- Martischnig, A., Voessner, S., & Stark, G. (2009). Agent based modeling and system dynamics in healthcare: Modeling two stage preventive medical checkup systems. International Conference on Agents and Artificial Intelligence. Proceedings of the International Conference on Agents and Artificial Intelligence (pp. 416–421).
- Melão, N., & Pidd, M. (2006). Using component technology to develop a simulation library for business process modelling. European Journal of Operational Research, 172(1), 163–178. https://doi.org/https://doi.org/10.1016/j.ejor.2004.09.033
- Merrill, J. A., Deegan, M., Wilson, R. V., Kaushal, R., & Fredericks, K. (2013). A system dynamics evaluation model: Implementation of health information exchange for public health reporting. Journal of the American Medical Informatics Association, 20(E1), e131–e138. https://doi.org/https://doi.org/10.1136/amiajnl-2012-001289
- Mgbemena, C., & Bell, D. (2016). Data-Driven customer behaviour model generation for agent based exploration. Proceedings of the 49th Annual Simulation Symposium. Pasadena.
- Montevechi, J., Silva Costa, R., Leal, F., & Pinho, A. F. & Jesus, J. T. (2009). Economic evaluation of the increase in production capacity of a high technology products manufacturing cell using discrete event simulation. Winter Simulation Conference. Proceedings of Winter Simulation Conference (pp. 2185–2196). Austin
- Montevechi, J. A. B., Leal, F., de Pinho, A. F., Costa, R. F., de Oliveira, M. L. M., & Da Silva, A. L. F. (2010). Conceptual modeling in simulation projects by mean adapted IDEF: An application in a Brazilian tech company. Winter Simulation Conference. Winter Simulation Conference (pp. 1624–1635). Baltimore.
- Montevechi, J. A. B., Pinho, A. F., De, Leal, F., & Marins, F. A. S. (2007). Application of design of experiments on the simulation of a process in an automotive industry. Winter Simulation Conference. Proceedings of Winter Simulation Conference. Washington.
- Moradi, S., Nasirzadeh, F., & Golkhoo, F. (2015). A hybrid SD–DES simulation approach to model construction projects. Construction Innovation, 15(1), 66–83. https://doi.org/https://doi.org/10.1108/CI-10-2013-0045
- Negahban, A., & Yilmaz, L. (2014). Agent-based simulation applications in marketing research: An integrated review. Journal of Simulation, 8(2), 129–142. https://doi.org/https://doi.org/10.1057/jos.2013.21
- Nicolae, O., Wagner, G., & Werner, J. (2010). Towards an executable semantics for activities using discrete event simulation. Business Process Management Workshops. BPM 2009. International Conference on Business Process Management (pp. 369–380). https://doi.org/https://doi.org/10.1007/978-3-642-12186-9_35
- Onggo, B. S. S. (2012). Bpmn pattern for agent-based simulation model representation. Winter Simulation Conference. Proceedings of Winter Simulation Conference (pp. 1–10). Berlin.
- Orji, I. J., & Wei, S. (2015). An innovative integration of fuzzy-logic and systems dynamics in sustainable supplier selection: A case on manufacturing industry. Computers and Industrial Engineering, 88, 1–12. https://doi.org/https://doi.org/10.1016/j.cie.2015.06.019
- Overmyer, S. P., Lavoie, B., & Rambow, O. (2001). Conceptual modeling through linguistic analysis using LIDA. 01 Proceedings of the 23rd International Conference on Software Engineering (pp. 401–410). Toronto, Ontario, Canada.
- Pace, D. K. (2000). Ideas about simulation conceptual model development. Johns Hopkins APL Technical Digest, 21(3), 327–336.
- Pace, D. K. (2002). The value of a quality simulation conceptual model. Modeling and Simulation Magazine, 1(1), 9–10.
- Pecek, B., & Kovacic, A. (2011). Business process management: Use of simulation in the public sector. Economic Research-Ekonomska Istraživanja, 24(1), 95–106. https://doi.org/https://doi.org/10.1080/1331677X.2011.11517447
- Pehrsson, L., Ng, A. H. C., & Stockton, D. (2013). Industrial cost modelling and multi-objective optimisation for decision support in production systems development. Computers & Industrial Engineering, 66(4), 1036–1048. https://doi.org/https://doi.org/10.1016/j.cie.2013.08.011
- Pereira, T. F., Montevechi, J. A. B., De Miranda, R. C., & Friend, J. D. (2015). Integrating soft systems methodology to aid simulation conceptual modeling. International Transactions in Operational Research, 22(2), 265–285. https://doi.org/https://doi.org/10.1111/itor.12133
- Perez-Mujica, L., Terry, B., Duncan, R., Andrea, R., Max, F. C., & Jonathon, H. (2014). Developing a sustainability assessment tool for socio-environmental systems: A case study. Int. Workshop on Simulation for Energy, Sustainable Development & Environment (pp. 83–91). Athens, Greece.
- Pisuchpen, R., & Chansangar, W. (2014). Modifying production line for productivity improvement: A case study of vision lens factory. Songklanakarin Journal of Science and Technology, 36(3), 345–357.
- Ramwadhdoebe, S., Buskens, E., Sakkers, R. J. B., & Stahl, J. E. (2009). A tutorial on discrete-event simulation for health policy design and decision making: Optimizing pediatric ultrasound screening for hip dysplasia as an illustration. Health Policy (Amsterdam, Netherlands), 93(2–3), 143–150. https://doi.org/https://doi.org/10.1016/j.healthpol.2009.07.007
- Robinson, S. (2008). Conceptual modelling for simulation Part I: Definition and requirements. Journal of the Operational Research Society, 59(3), 278–290. https://doi.org/https://doi.org/10.1057/palgrave.jors.2602368
- Robinson, S. (2011). Conceptual modeling for simulation: definition and requirements. In S. Robinson, R. Brooks, K. Kotiadis, & D.-J. Van der Zee (Eds.), Conceptual modeling for discrete-event simulation (pp. 3–30). Taylor & Francis Group.
- Robinson, S. (2013). Conceptual modeling for simulation. Winter Simulation Conference. Proceedings of Winter Simulation Conference (pp. 377–388). Washington.
- Robinson, S. (2015). A tutorial on conceptual modeling for simulation. Winter Simulation Conference (pp. 1820–1834). Huntington Beach, CA, USA.
- Robinson, S., Arbez, G., Birta, L. G., & Tolk, A. (2015). Conceptual modeling: Definition, purpose and benefits. Winter Simulation Conference (pp. 1558–4305). Huntington Beach, CA, USA.
- Roca, R., Pace, D., Robinson, S., Tolk, A., & Yilmaz, L. (2015). Paradigms for conceptual modeling. Proceedings of the 48th Annual Simulation Symposium (pp. 202–209). Alexandria, Virginia.
- Rossheim, R. J. (1963). Report on proposed american standard flowchart symbols for information processing. Communications of the ACM, 6(10),599–604. https://doi.org/https://doi.org/10.1145/367651.367657
- Sahaf, Z., Garousi, V., Pfahl, D., Irving, R., & Amannejad, Y. (2014). When to automate software testing? Decision support based on system dynamics: An industrial case study. ICSSP. ACM International Conference Proceeding Series (pp. 149–158).
- Sajjad, M., Singh, K., Paik, E., & Chang-Won, A. (2016). Social simulation: The need of data-driven agent-based modelling approach. 18th International Conference on Advanced Communication Technology (ICACT) (pp. 818–821). Pyeongchang, South Korea.
- Sandanayake, Y. G., Oduoza, C. F., & Proverbs, D. G. (2008). A systematic modelling and simulation approach for JIT performance optimisation. Robotics and Computer-integrated Manufacturing, 24(6), 735–743. https://doi.org/https://doi.org/10.1016/j.rcim.2008.03.013
- Sargent, R. G. (2013). Verification and validation of simulation models. Journal of Simulation, 7(1), 12–24. https://doi.org/https://doi.org/10.1057/jos.2012.20
- Schönemann, M., Herrmann, C., Greschke, P., & Thiede, S. (2015). Simulation of matrix-structured manufacturing systems. Journal of Manufacturing Systems, 37(1), 104–112. https://doi.org/https://doi.org/10.1016/j.jmsy.2015.09.002
- Sharda, B., & Bury, S. J. (2011) Best practices for effective application of discrete event simulation in the process industries. Winter Simulation Conference. Proceedings of Winter Simulation Conference (pp. 2320–2329).
- Shengqiang, L., Wilsun, X., & Xiaodong, L. (2014). Dynamic model for paper mills facilities using template-based load modeling technique. 2014 IEEE/IAS 50th Industrial & Commercial Power Systems Technical Conference (pp. 1–11). Fort Worth.
- Sobolev, B., Harel, D., Vasilakis, C., & Levy, A. (2008). Using the Statecharts paradigm for simulation of patient flow in surgical care. Health Care Management Science, 11(1), 79–86. https://doi.org/https://doi.org/10.1007/s10729-007-9026-7
- Sousa, G. W. L., Carpinetti, L. C. R., Groesbeck, R. L., & Alken, E. V (2005). Conceptual design of performance measurement and management systems using a structured engineering approach. International Journal of Productivity and Performance Management, 54(5/6), 385–399. https://doi.org/https://doi.org/10.1108/17410400510604548
- Squires, H., Chilcott, J., Akehurst, R., Burr, J., & Kelly, M. P. (2016). A framework for developing the structure of public health economic models. Value in Health, 19(5), 588–601. https://doi.org/https://doi.org/10.1016/j.jval.2016.02.011
- Stainsby, H., Taboada, M., & Luque, E. (2009). Towards an agent-based simulation of hospital emergency departments. 2009 IEEE International Conference on Services Computing. 2009 IEEE International Conference on Services Computing (536–539). http://ieeexplore.ieee.org/document/5283900/
- Tako, A. A., & Kotiadis, K. (2015). PartiSim: A multi-methodology framework to support facilitated simulation modelling in healthcare. European Journal of Operational Research, 244(2), 555–564. https://doi.org/https://doi.org/10.1016/j.ejor.2015.01.046
- Topping, C. J., & Odderskaer, P. (2004). Modeling the influence of temporal and spatial factors on the assessment of impacts of pesticides on skylarks. Environmental Toxicology and chemistry/SETAC, 23(2), 509–520. https://doi.org/https://doi.org/10.1897/02-524a
- Tranfield, D., Denyer, D., & Smart, P. (2003). Towards a methodology for developing evidence-informed management knowledge by means of systematic review. British Journal of Management, 14(3), 207–222. https://doi.org/https://doi.org/10.1111/1467-8551.00375
- Walton, B., Nawarathna, B., George, B. A., & Malano, H. M. (2009). Future water supply and demand assessment in peri-urban catchments using system dynamics approach. 18th World IMACS Congress and MODSIM09. International Congress on Modelling and Simulation: Interfacing Modelling and Simulation with Mathematical and Computational Sciences, Proceedings (pp. 3872–3878).
- Wang, B., Brême, S., & Moon, Y. B. (2015). Conceptual modelling and the project process in real simulation projects: A survey of simulation modellers. Journal of Computers and Industrial Engineering, 66(10), 1669–1685. https://doi.org/https://doi.org/10.1016/j.cie.2013.12.016
- Wang, W., & Brooks, R. (2015). Conceptual modelling and the modelling process in simulation projects: A survey of simulation modellers. Journal of the Operational Research Society, 66(10), 1669–1685. https://doi.org/https://doi.org/10.1057/jors.2014.128
- Wang, W., & Brooks, R. J. (2007). Empirical investigations of conceptual modeling and the modeling process. Winter Simulation Conference. Proceedings of Winter Simulation Conference (pp. 762–770). Washington.
- Watson, P. F., & Petrie, A. (2010). Method agreement analysis: A review of correct methodology. Theriogenology, 73(9), 1167–1179. https://doi.org/https://doi.org/10.1016/j.theriogenology.2010.01.003
- Williams, E. J., & Ülgen, O. M. (2012). Pitfalls in managing simulation project. Winter Simulation Conference (pp. 1219–1229). Berlin, Germany.
- Yang, Z., & Liyi, Z. (2011). System dynamics modeling and simulation of information resources allocation of R&D cooperation in China. International Journal of Digital Content Technology and Its Applications, 5(2), 21–33. https://doi.org/https://doi.org/10.4156/jdcta.vol5.issue2.3
- Yuriy, G., & Vayenas, N. (2008). Discrete-event simulation of mine equipment systems combined with a reliability assessment model based on genetic algorithms. International Journal of Mining, Reclamation and Environment, 22(1), 70–83. https://doi.org/https://doi.org/10.1080/17480930701589674
- Zeigler, B. P., & Hammonds, P. E. (2007). Modeling & simulation-based data engineering: Introducing Pragmatics into ontologies for net-centric information exchange (1st ed.). Elsevier Academic Press.
- Zhou, M., Zhang, Q., & Chen, Z. (2006). What can be done to automate conceptual simulation modeling? (pp. 809–814) Winter Simulation Conference. Proceedings of Winter Simulation Conference, Monterey.
- Zou, Y., Yao, Y., Jiang, Z., & Tang, W. (2016). An overview of conceptual model for simulation. In L. Zhang, X. Song, Y. Wu (eds), Theory, Methodology, Tools and Applications for Modeling and Simulation of Complex Systems. AsiaSim 2016, SCS AutumnSim 2016. Communications in Computer and Information Science (pp. 96–100). https://doi.org/https://doi.org/10.1007/978-981-10-2663-8_10
- Zulkepli, J., & Mustafee, N. (2012). Hybrid simulation for modelling large systems: An Example of integrated care model. Winter Simulation Conference. Proceedings of Winter Simulation Conference. (pp. 1–12).Berlin.
- Zupan, H., & Herakovic, N. (2015). Production line balancing with discrete event simulation: A case study. IFAC-papersonline, 48(3), 2305–2311. https://doi.org/http://dx.doi.org/10.1016/j.ifacol.2015.06.431