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The course aims to teach the basic principles and the methods in developing simulation models. The goal is to teach simulation modeling with a simulation package, ARENA including the design of the simulation experiments and statistical analysis of the input and output data for simulation models.
Decision making under uncertainty. Dynamic programming. Introduction to stochastic processes. Queuing models and applications. Markov chains and Markov processes. Game theory.
Upon succesful completion of this course, a student will be able to
1. Apply the basic concepts in discrete-event simulation modeling including model components, event list and flowchart. [e][B3]
2. Use simulation techniques and tools to model systems. [e, k][B3]
3. Construct simulation models using a simulation package and conduct simulation experiments. [b1, e] [B3]
4. Analyse the input and output data for simulation models. [b2][B4]
5. Perform verification and validation - for simulation models. [b2, e] [B3]
6. Identify engineering problems by using performance measures of simulation models. [e][B1]
7. Analyze solutions for industrial engineering problems and compare design alternatives by using simulation techniques. [e, b2][B4]