- Undergraduate course:
- ISE 441: Introduction to Simulation
- This course is a first-level introductory course to (spreadsheet and discrete-event) simulation modeling and (input and output) analysis through two softwares: @Risk and Simio.
- Is this the right course for you? The concepts are heavily based on statistical inference and probability; hence ISE 362 or equivalent is a pre-requisite.
- Master’s and PhD level courses:
- ISE/OR 562: Simulation Modeling
- This course is similar to ISE 441 with more depth in software use, recommended for Master’s students.
- Is this the right course for you? If you have already taken ISE 441, this course may be largely repetitive for you.
- ISE/OR 762: Stochastic Simulation
- Introductory level Monte Carlo course, recommended for PhD students, with methodological approach to simulation. If you are looking to build discrete-event simulation models with commercial software, consider taking ISE 562.
- Is this the right course for you? If you are working on a problem that involves a simulation model either being constructed with programming or with accessible code for running experiments and making adjustments, this course is for you. This is not a software course and commercial simulation is not discussed. ISE/OR762 considers simulation as a way of doing probability analysis by performing statistical experiments, so both probability and statistics are central to the course. It will teach you about the principles and elements of a Monte Carlo simulation. The concepts are also valuable for machine learning, likening the learning algorithm to a black box simulation. The main topics involve discrete-event simulation, input modeling and random process generation, output analysis, and variance reduction.
- ISE/OR 772: Advanced Stochastic Simulation
- Advanced Monte Carlo course with focus on simulation optimization in different settings. Consider taking this course after ISE 762.
- Is this the right course for you? If you have successfully completed ISE/OR 762 and seek an in-depth exploration of cutting-edge simulation concepts, this course is for you. ISE/OR 772 delves into advanced simulation topics, emphasizing optimization in continuous and discrete spaces, ranking and selection, and multi-objective optimization through simulation. Time permitting, the syllabus covers topics such as advanced output analysis involving batching and bootstrapping, derivative and density estimation, metamodeling and global optimization, rare-event simulation, and input uncertainty and robustness. Students will engage in intensive reading of journal articles and enhance their ability to comprehend technical scholarly writing through required writing and presentations.
