Laura S. Aragone

Solving minimax control problems via nonsmooth optimization

We address minimax optimal control problems with linear dynamics. Under convexity assumptions, by using non-smooth optimization techniques, we derive a set of optimality conditions for the continuous-time case. We define an approximated discrete-time problem where analogous conditions hold. One of them allows us to design an easily implementable descent method. We analyze its convergence and we show some preliminary numerical results.

Fully discrete schemes for monotone optimal control problems

In this article, we study an infinite horizon optimal control problem with monotone controls. We analyze the associated Hamilton–Jacobi–Bellman (HJB) variational inequality which characterizes the value function and consider the totally discretized problem using Lagrange elements to approximate the state space

Numerical approximation of optimization problems with L functionals

\Omega

Solution of a minimax problem with additive final cost

Ω. The convergence orders of these approximations are proved, which are in general

Penalization techniques in L INFINITY optimization problems with unbounded horizon

(h+\frac{k}{\sqrt{h}})^\gamma

A Fast Computional Procedure to Solve The Multi-Item Single Machine Lot Scheduling Optimization Problem

(h+kh)γ where