Modelling and Simulation Concepts

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By: Hans Vangheluwe


At a first glance, it is not easy to characterize modelling and simulation. Certainly, a variety of application domains such as fluid dynamics, energy systems, and logistics management make use of it in one form or another. Depending on the context, modelling and simulation is often seen as a sub-set of Systems Theory, Control Theory, Numerical Analysis, Computer Science, Artificial Intelligence, or Operations Research. Increasingly, modelling and simulation integrates all of the above disciplines. Recently, modelling and simulation has been slated to become the computing paradigm of the future. As a paradigm, it is a way of representing problems and thinking about them, as much as a solution method. The problems span the analysis and design of complex dynamical systems. In analysis, abstract models are built inductively from observations of a real system. In design, models deductively derived from a priori knowledge are used to build a system, satisfying certain design goals. Often, an iterative combination of analysis and design is needed to solve real problems. Though the focus of modelling and simulation is on the behaviour of dynamical (i.e., time-varying) systems, static systems (such as entity-relationship models and class diagrams, described in the Unified Modelling Language UML [RJB99]) are a limit-case. Both physical (obeying conservation and constraint laws) and non-physical (informational, such as software) systems and their interactions are studied by means of modelling and simulation.

Link to material: http://www.cs.mcgill.ca/~hv/classes/MS/MSconcepts.pdf

Link to Slideshows: http://www.cs.mcgill.ca/~hv/classes/MS/lecture.MSconcepts.pdf


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