By the end of the module student should be able to: (i) develop dynamic tools for systems thinking including methods to elicit and map the structure of complex systems; (ii) to develop tools for modeling and dynamic simulation of complex systems; (iii) apply procedures for testing and improving the simulation models; (iv) design and evaluate policies for improving the dynamic behavior of systems.
Course Content (Syllabus)
Introduction: fundamental system concepts; the object of a system dynamics analysis.
System Structure and Dynamic Behavior: open and closed systems; positive-negative feedback loop; S-curve dynamics; oscillation, overshoot and collapse; other modes of behavior.
Causal-Loop Diagrams: construction principles; loop identification.
Stocks and Flows: diagramming notation; mathematical formulation; stocks and flows diagrams; graphical integration.
Mathematical Formulation of Positive Feedback Loop: analytical solution for the linear first-order system; doubling times; non linear systems.
Mathematical Formulation of Negative Feedback Loop: analytical solution for the linear first-order system; time constants and half-times; zero-value goal structure; initial conditions; system compensation.
Mathematical Formulation of S-shaped Growth: Verhulst growth; Richards’ model; Weibull model.
Modeling Decision Making: principles for modeling decision making; formulating rate equations.
Delays: material delays; information delays; estimating the duration and distribution of delays.
Introduction to PowerSim Software Package: flow diagram modeling; defining the time; computational sequence; overview of operators; function definitions.
Case Studies in Industrial Management Using the System Dynamics Approach (PowerSim models).
System dynamics, dynamic simulation, modelling and analysis, powersim.