Public Courses

This simulation course is for operations research analysts and systems analysts who would like to use simulation to design and optimize real-world systems. It presents methods for developing a simulation model, ensuring its validity, choosing simulation software, selecting input probability distributions, and analyzing simulation runs.

This simulation course discusses practical statistical techniques for comparing alternative system designs, variance-reduction techniques for obtaining more precise comparisons for the same amount of computing, the use of experimental design techniques to determine important system factors, simulation-based optimization, and agent-based simulation.

This simulation course presents a discussion of practical techniques for validating your models and simulations. All techniques will be illustrated by examples based on actual simulation projects.  At the end of the seminar, each attendee will be familiar with "the" twelve fundamental validation techniques and know how to apply them.

Simulation models often have many input factors and determining which ones are really important can be quite difficult. We give a comprehensive presentation of design of experiments specifically for simulation modeling, whose major goal is to determine which factors have the greatest effect on the responses.

This simulation course provides a comprehensive introduction to agent-based simulation, where autonomous agents interact with each other and their environment over time. An agent’s behavior can depend on the current and past states of its environment, permitting much more complex behaviors to be represented.