SYST 302: Systems Methodology and Design

#### Professor Terry L. Friesz

email:
tfriesz@gmu.edu

**HOMEWORK and EXAMS:**
Homework will be assigned and randomly graded; homework will be the primary source
of questions for the exams. There will be two midterm exams and a final exam.
The exams will be in-class exams. See “Special Information” below.

**GRADING:** Your
homework will constitute 25% of you grade; each of the three exams will
constitute 25%. You will also be expected to participate in classroom
discussions; students who are unprepared for such discussions will have points
deducted from their exams/homework average score.

**RECOMMENDED TEXT:**
The following text is recommended but by no means required:

1. Blanchard and Fabrycky:
Systems Engineering and Analysis, 3rd edition, Prentice-Hall, 1998

**REQUIRED SOFTWARE:** You must have Matlab.
You must learn how to use the following special features of MatLab:
the Optimization Toolbox, the ODE solver, the PDE solver and Simulink.

**IMPRORTANCE OF
LECTURES:** Lectures will be the single most important source of information.
Although there are no explicit penalties for missing a lecture, students who
miss the lectures will likely be unable to fully comprehend the material and will
likely do extremely poorly on exams. Much of each classroom presentation is
extemporaneous and geared to the particular difficulties of the class on the
day of the lecture; as a consequence your own personal notes are of great
importance.

OUTLINE

1. key
types of mathematical problems encountered in systems analysis and design

2. foundations
of mathematical programming

3. microeconomics:
theory of the consumer

4. microeconomics:
theory of the firm

5. equilibria
and games

6. economic
planning and market design

7. review
of ordinary differential equations

8. transform
methods

9. traditional
engineering economics

10. example
mathematical programming applications

11. foundations
of dynamic optimization

12. example
dynamic optimization applications

13. capital
budgeting

14. project
time phasing

15. network
design

16. a
first look at partial differential equations

17. elements
of probability theory and stochastic processes

18. reliability
and stochastic programming

19. a
first look at stochastic differential equations

20. financial
engineering