Evaluation and Ranking of Discrete Simulation Tools

[1] M.C. Albrecht, and P.E. AZ, “Introduction to discrete event simulation”, available http://www.albrechts.com/mike/DES/index.html, 2010.

[2] T.M.K. Roeder, “An information taxonomy for discrete event simulations,” Ph.D. Dissertation, University of California, Berkeley, 2004.

[3] H. Rashidi, “Discrete simulation tools: A survey on taxonomies,” Journal of Simulation, vol. 4, pp. 1-11, 2016.

[4] C.M. Overstreet, “Model specification and analysis for discrete event simulation,” Ph.D. Dissertation, Department of Computer Science, Virginia Polytechnic Institute and State University, 1982.

[5] R.T. Ahmed, Hall and P. Wernick, “A proposed framework for evaluating software process simulation models,” Proceedings Prosim’03 May 3 -4, Portland state University, 2003.

[6] R.E. Nance, “A history of discrete event simulation programming languages,” ACM SIGPLAN Notices, vol. 28, no. 3, 1993, pp. 149-175.

[7] J. Banks, and R. Gibson, “Selecting simulation software,” IIE Solutions, pp. 30-32, 1999.

[8] C.M. Overstreet, and R. E. Nance, “Characterizations and relationships of world views,” in Proceedings of the 2004 Winter Simulation Conference, Edited by R.G. Ingalls,M. D. Rossetti, J. S. Smith, and B. A. Peters, 2004, pp. 279-287.

[9] A. Sulistio, C. Shinyeo, and R. Buyya, “Taxonomy of computerbased simulations and its mapping to parallel and distributed systems simulation tools,” Software Practice and Experience, vol. 34, pp. 653–673, 2004.

[10] W. Wang, Y. Zhu, and Q. Li, “Service-oriented simulation framework: an overview and unifying methodology,” Ph.D. dissertation, Changsha, China: National University of Defence Technology, 2010.

[11] S. Suliza, R. Ibrahim, N. H. Zakaria, and A. H. Ab Hami, “comparing three simulation model using taxonomy: system dynamic simulation, discrete event simulation and agent based simulation,” International Journal of Management Excellence, vol. 1, no. 3, 2013, pp. 53-59.

[12] G.T. Mackulak, J.K. Cochran, and P.A. Savory, “Ascertaining important features for industrial simulation environments,” Simulation, vol. 63, no. 4, pp. 211–221, 1994.

[13] E.H. Page, “Simulation modeling methodology principles and etiology of decision support,” Ph.D. Dissertation, Virginia Polytechnic Institute and State University, 1994.

[14] V. Hlupic, Z. Irani, and R. J. Paul, “Evaluation framework for simulation software,” International Journal of Advanced Manufacturing Technology, vol. 15, no. 5, pp. 366-382, 1999.

[15] V. Hlupic and R.J. Paul, “Guidelines for selection of manufacturing simulation software,” IIE Transactions, vol. 31, no. 1, pp. 21-29, 1999.

[16] T.W. Tewoldeberhan, A. Verbraeck, E. Valentin, and G. Bardonnet, “An evaluation and selection methodology for discrete-event simulation software,” Proceedings of the Winter Simulation Conference, 2002, vol. 1, pp 67- 75.

[17] A.F. Seila, V. Ceric, and P. Tadikamalla, Applied simulation modeling, Thomson Learning, Australia: Thomson Learning, 2003.

[18] B. Boehm, Software Engineering Economics, Prentice Hall Inc, 1981.

[19] O.V. Lindland, G. Sindre, and A. Solvberg, “Understanding quality in conceptual modeling,” IEEE Software, pp. 42- 49,1994.

[20] B. Kitchenham, L. Picakrd, S. Linkman, and P. Jones, “A framework for evaluating software bidding model,” Proceedings of Conference on Empirical Assessment in Software Engineering, April 2002.

[21] L.W. Schruben, “Mathematical programming models of discrete event system dynamics,” Proceedings of the 2000 Winter Simulation Conference, Edited by J. A. Jones, R. R. Barton, K. Kang, and P. A. Fishwick, Piscataway, NJ, USA: IEEE, 2000, pp. 381-385.

[22] A.S. Jadhava and R.M. Sonar, "Evaluating and selecting software tools: A review," Journal of Information and Software Technology, vol. 51, no. 3, pp. 555-563, 2009.

[23] A. Guptal, K. Singh, and R. Verma, “A critical study and comparison of manufacturing simulation softwares using analytic hierarchy process,” Journal of Engineering Science and Technology, vol. 5, no. 1, pp. 108–129, 2010.

[24] OR/MS Today, “Simulation software survey”, available http://www.ormstoday.org/surveys/Simulation/Simulation.h tml, 2016.

[25] M. Jadrić, M. Ćukušić, A. Bralić, “Comparison of discrete event simulation tools in an academic environment,” Croatian Operational Research Review, vol. 5, no.2, pp. 203-219, 2014.

[26] A. Gupta, “How to select a simulation software,” International Journal of Engineering Research and Development, vol. 10, no. 3, pp. 35-41, 2014.

[27] N. Damij, P. Boškoski, M. Bohanec, and B. Mileva Boshkoska, “Ranking of business process simulation software tools with dex/qq hierarchical decision model,” Journal of PLoS One, vol. 11, no. 2, pp. 1-16, 2016.

[28] J. W. Fowler, L. Mönch, “A comparison of discrete-event simulation approaches for complex manufacturing systems and healthcare systems,” Simulation in Production and Logistics, pp. 447-457, 2015.

[29] L.W. Schruben and T. M. Roeder, “Fast simulations of largescale highly congested system Simulation,” Transactions of the Society for Modeling and Simulation International. vol. 79, no. 3, pp. 1-11, 2003.

[30] F.Y. Partovi, J. Burton, and A. Banerjee, “Application of analytical hierarchy process in operations management,” International Journal of Operations and Production Management, vol. 10, no. 3, pp. 5-19, 1990.

[31] F. Zahedi, “The Analytic Hierarchy Process – A survey of the method and its applications,” Journal of Interfaces, vol. 16, no. 4, pp. 96-108, 1986.

[32] T.L. Saaty and P.C. Rogers, “Higher education in the United State (1985-2000) scenario construction using a hierarchical framework with eigenvector weighting,” Socio-economic Planning Sciences, vol. 10, no. 6, pp. 251-263, 1976.