Course Description: This is a survey course designed
to introduce students to both deterministic and stochastic models used to
help managers make more informed decisions. It provides the foundations
for more intensive study in such fields as industrial engineering,
transportation, computer science and business. The scope is broad, and
because the material is introductory in nature, it is suitable for
graduate students with varied technical backgrounds.
Course Objectives:
Students will:
- Become knowledgeable in the problem solving process
- Learn how to develop mathematical models for analyzing industrial-socio-economic systems
- Learn the differences between deterministic and stochastic models and the uses of each
- Gain an appreciation for the strengths and weaknesses of the various analytic techniques that are used in strategic planning and systems design
- Understand the level of difficulty associated with solving real-world problems
- Learn how to use modern software tools to solve manufacturing, scheduling, network design, engineering design, reliability, and queuing problems
Course Outline by Topical Areas:
The following topics will be covered in the order given
- Operations research
- Linear programming
- Classic linear programming examples
- Network flow programming
- Integer programming
- Staff scheduling at the USPS mail procressing distribution centers
- Nonlinear programming models
- Introduction to probability
- Stochastic processes
- Discrete-time Markov chains
- Queuing systems
- Queuing networks
Prerequisites
- Differential calculus
- Basic Understanding of linear algebra and matrix operations
- Introductory course in probability and statistics
