Overview
Description
System dynamics, discrete-event simulation, agent-based modeling, optimization, and experimental design. Students will learn to develop and analyze models to simulate and optimize complex systems in manufacturing, service, and supply chain industries. Emphasis on model building, application of basic statistical data analysis, and the use of simulation for design, evaluation, and improvement of such systems. Introduction to available software. Case studies.
Requirements
Recommended Preparation
- Numerical methods and programming fundamentals
Original catalog text
Recommended Preparation
Recommended Preparation: Numerical methods and programming fundamentals
Units
Lecture3
Catalog Details
Offering
Offered: Every Fall
Terms
fall
Attributes
Standard
Learning Outcomes
- apply engineering research and theory to advance the art, science, and practice of the discipline.
- design and conduct experiments as well as to analyze, interpret, apply, and disseminate the data.
- have an understanding of research methodology.
- develop simulation models using different techniques.