Vue d'ensemble
G茅nie 茅lectrique : General introduction to optimization methods including steepest descent, conjugate gradient, Newton algorithms. Generalized matrix inverses and the least squared error problem. Introduction to constrained optimality; convexity and duality; interior point methods. Introduction to dynamic optimization; existence theory, relaxed controls, the Pontryagin Maximum Principle. Sufficiency of the Maximum Principle.
Terms: Hiver 2025
Instructors: Radhakrishnan, Sindhu (Winter)
