Numerical Algorithms for Deterministic Impulse Control Models with Applications

Numerical methods for optimal control problems: algorithms, analysis and applications

Numerical algorithms for R&D stochastic control models

We consider the optimal strategy of R&D expenditure adopted by a firm that engages in R&D to develop an innovative product to be launched in the market. The firm faces with technological uncertainty associated with the success of the R&D effort and market uncertainty of the stochastic revenue flow generated by the new product. Our model departs from most R&D models by assuming that the firm’s k...

Optimal Control Lecture 9 : Numerical Methods for Deterministic Optimal Control

Lecturer: Marin Kobilarov Consider the general setting where we are minimizing J = φ(x(t f), t f) + t f t 0 L(x(t), u(t), t)dt, (1) subject to: x(t 0) = x 0 , x(t f) and t f free (2) ˙ x(t) = f (x(t), u(t), t) (3) c(x(t), u(t), t) ≤ 0, for all t ∈ [t 0 , t f ] (4) ψ(x(t f), t f) ≤ 0, (5) We will consider three families of numerical methods for solving the optimal control problem: • dynamic prog...

A review of dough rheological models used in numerical applications

The motivation for this work is to propose a first thorough review of dough rheological models used in numerical applications. Although many models have been developed to describe dough rheological characteristics, few of them are employed by researchers in numerical applications. This article reviews them in detail and attempts to provide new insight into the use of dough rheological models.

Deterministic Models for Internet Congestion Control

There has been a lot of recent work on decentralized end-to-end congestion control algorithms for the Internet. These are based on ECN marking with the goal of building a low-loss, low-queueing-delay network. The control algorithms are designed on the premise that each user has a utility function, which the user is trying to maximize, while the network is simultaneously trying to maintain some ...