An introduction to the key aspects of operations research methodology. Students will model and and solve a variety of problems using deterministic and stochastic operations research techniques. Topics include basic theory, modeling, the use of computer tools, and interpreting results.
Nature of the Course
This course is designed to give students who are new to operations research an appreciation for and understanding of what the methods are and how they are used, as well as the sort of results they can yield. It also provides a common framework for students planning to take any of the many other graduate-level operations research courses. While the course covers essential theory, there is also an emphasis on developing a feel for operations research and improving students' modeling skills.
This course presents the fundamental approaches common to all industrial engineering operational research techniques as well as central themes in each of the major areas of specialization:
While these areas are covered in much greater detail in specialized courses, such as IE 515 (Markov Processes), IE 522 (Queueing systems), IE 525 (System Synthesis and Design), IE 527 (Industrial Scheduling and Sequencing), IE 533 (Linear Programming), IE 534 (Non-linear Programming), IE 535 (Discrete Optimization), IE 567 (Basic Simulation Modeling and Analysis), IE 568 (Advanced Simulation Modeling and Analysis), and IE 569 (Stochastic Simulation Concepts and Techniques), this course provides an overview of the entire suite of techniques and some idea of how the elements fit together.
In each area, the following will be covered:
Additionally, after each of the areas have been covered, the super-problem of deciding which specialized area is best to use in selected situations will be addressed.
Who should take this course: This course is intended for graduate students who are interested in operations research, but are not sure which areas of specialization to concentrate in. It is also suitable for those who have taken the specialized courses and wish to integrate the separate bodies of knowledge. It is highly recommended for graduate students who have not had a formal introduction to operations research similar to that experienced by IE undergraduate majors.
Expected Background: The student should have at least a familiarity with matrix algebra, integral and differential calculus, and a first course in calculus-based probability and statistics.
|Text:||Introduction to Operations Research by Hillier and Lieberman, 8th ed., 2005. ISBN 13-9780073211145.|
Revision Date: November 14, 2008 by jpm.