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Publisher: Operational Research Society
Languages: English
Types: Part of book or chapter of book
Subjects:
The supply chain can be a source of competitive advantage for the firm. Simulation is an effective tool for investigating supply chain problems. The three main simulation approaches in the supply chain context are System Dynamics (SD), Discrete Event Simulation (DES) and Agent Based Modelling (ABM). A sample from the literature suggests that whilst SD and ABM have been used to address strategic and planning problems, DES has mainly been used on planning and operational problems., A review of received wisdom suggests that historically, driven by custom and practice, certain simulation techniques have been focused on certain problem types. A theoretical review of the techniques, however, suggests that the scope of their application should be much wider and that supply chain practitioners could benefit from applying them in this broader way.
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    • H. A. Akkermans and N. Dellaert (2005). “The rediscovery of industrial dynamics: the contribution of system dynamics to supply chain management in a dynamic and fragmented world” System Dynamics Review, 21, 3: 173- 186.
    • B. Angerhofer and M. Angelides (2000). “System Dynamics Modeling in supply Chain Management” Proceedings of the 2000 Winter Simulation Conference.
    • P. Ball (1994). PhD Thesis, Aston University, “Design of an expandable manufacturing simulator through the application of objectoriented principles.”
    • S. Biswas and Y.Narahari (2003). “Object Oriented Modelling and Decision Support for Supply Chains” European Journal of Operational Research, 153, 3, 704-726.
    • A. Borshchev and A. Fillipov (2004). “From System Dynamics and Discrete Event to Practical Agent Based Modelling: Reasons, Techniques, Tools” 22nd International Conference of the System Dynamics Society, 2004.
    • S. Brailsford and N.Hilton (2001). “A comparison of discrete event simulation and system dynamics for modelling healthcare systems”. In: Riley J. (ed). Proceedings of ORAHS 2000. Glasgow: Scotland pp 18-39.
    • S. Cavalieri and S. Terzi (2004). “Simulation in the supply chain context: a survey” Computers in Industry, 53: 3-16.
    • M. Christopher (2005), Logistics and Supply Chain Management, Prentice-Hall.
    • S. Chopra and P. Meindl (2007), Supply Chain Management, Prentice-Hall.
    • R. Coyle (1985). “Representing discrete events in system dynamics models”, Journal of Operational Research Society, Vol 36, No 4.
    • J. Forrester (1958). “Industrial Dynamics - A Major Breakthrough for Decision Makers”, Harvard Business Review, 36, 4: 37-66.
    • J. Forrester (1961). Industrial Dynamics, MIT Press.
    • A. Greasley (2007). "Approaches to Incorporating Human Behaviour into a Discrete-Event Simulation Study", SCMIS 2007.
    • J. Homer (1999). “Macro and micro modelling of field service dynamics”, System Dynamics Review, Vol 15, No 2.
    • P. Kiviat (1969). “Digital computer simulation: Computer programming languages”, RAND Memo, RM-5883-PR, RAND Corporation, Santa Monica, California.
    • T. Kuhn (1996), The Structure of Scientific Revolutions, Chicago University Press.
    • M. Lackner (1962). “Toward a general simulation capability”, Proceedings of AFIPS Spring Joint Computer Conference, 1-14, San Francisco, California.
    • D. Lane (2000). “You just don't understand me: Modes of failure and success in the discourse between system dynamics and discrete event simulation”, LSE Working Paper 00.34.
    • T. Lorenz and A. Jost (2006). “Towards an orientation framework in multi-paradigm modelling”, 23rd International Conference of the System Dynamics Society, Nijmegen 2006.
    • H. Min and G Zhou (2002). “Supply chain modeling: past, present and future”, Computers & Industrial Engineering, Volume 43, Issues 1-2.
    • J. Morecroft and S. Robinson (2005). “Explaining Puzzling Dynamics: Comparing the Use of System Dynamics and Discrete Event Simulation” 23rd International Conference of the System Dynamics Society, Boston.
    • M. North and C. Macal (2007). Managing Business Complexity, Oxford University Press.
    • J. Odell (2002). “Objects and Agents Compared”, Journal of Object Technology, Vol. 1, No. 1.
    • M. Pidd (2004). Computer Simulation in Management Science, 5th Ed. Wiley & Sons, Ltd.
    • C. Riddalls et al (2000), “Modelling the dynamics of supply chains”, International Journal of Systems Science.
    • N. Schieritz, and P. Milling (2003). “Modelling the Forest or Modelling the Trees, A comparison of System Dynamics and Agent Based Simulation”, 21st International Conference of the System Dynamics Society, New York.
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