OPTIMIZATION UNDER CONSTRAINTS
Theory and Applications of Nonlinear Programming

Contents:

1. First Thoughts on maximization

2. Constrained maximization and Lagrangian methods

3. The strong Lagrangian principle: Convexity

4. Linear programming

5. Some particular linear problems

6. Some problems with Linear constraints, I

7. Some problems with Linear constraints, II

8. Nonlinear constraints and stochastic effects

9. Numerical methods

10. Vector maximization problems