Conjugate Duality and Optimization
Provides a relatively brief introduction to conjugate duality in both finite- and infinite-dimensional problems. An emphasis is placed on the fundamental importance of the concepts of Lagrangian function, saddle-point, and saddle-value. General examples are drawn from nonlinear programming, approximation, stochastic programming, the calculus of variations, and optimal control.
Product details
January 1987Paperback
9780898710137
80 pages
255 × 178 × 5 mm
0.35kg
This item is not supplied by Cambridge University Press in your region. Please contact Soc for Industrial & Applied Mathematics for availability.
Table of Contents
- The Role of Convexity and Duality
- Examples of Convex Optimization Problems
- Conjugate Convex Functions in Paired Spaces
- Dual Problems and Lagrangians
- Examples of Duality Schemes
- Continuity and Derivatives of Convex Functions
- Solutions to Optimization Problems
- Calculating Conjugates and Subgradients
- Integral Functionals