1	Unconstrained Optimization.
2	Conditions for local minima,structure and algorithmic properties of methods.
3	Descent methods, conjugate gradient method.
4	Newton and quasi-Newton methods.
5	Constrained Optimization.
6	Linear programming.
7	Simplex method.
8	Duality theory .
9	Nonlinear programming .Midterm Exam.
10	Lagrange multipliers.
11	Kuhn-Tucker conditions.
12	Nonlinear constrained optimization .
13	Quadratic programming, active set methods.
14	Multiplier and other penalty functions.

1- Rangarajan K. Sundaram, a First Course in Optimization Theory, Cambridge University Press 1996.
2- S.S. Rao, Engineering Optimization: Theory and Practice, Third Edition, John Wiley & Son, New York, 1996.
3- J.S. Arora, Introduction to Optimum Design, McGraw-Hill, New York, 1989.