Description

1º Module - Software
VBA/EXCEL;Octave/Matlab;Aspen Plus.
 

2º Module - Numerical analysis complements
Solving numerically algebraic equations (Methods: Newton and Secant).
Matrices and algebraic equations systems.
Solving numerically ODE (Methods: Euler, Runge-Kutta, etc.).
Solving stiff ODE.
 

3º Module - Optimization
Introduction
One dimensional optimization (Methods: Newton, golden-section search, etc.).
Multidimensional unconstrained and constrained optimization (Methods: gradient, random search, Hooke-Jeeves, etc.).
Optimization and curve fitting by least squares.
Introduction to multiobjective optimization

Instructors

Florinda Figueiredo Martins

Contents

1º Module - Software
VBA/EXCEL;Octave/Matlab;Aspen Plus.
 

2º Module - Numerical analysis complements
Solving numerically algebraic equations (Methods: Newton and Secant).
Matrices and algebraic equations systems.
Solving numerically ODE (Methods: Euler, Runge-Kutta, etc.).
Solving stiff ODE.
 

3º Module - Optimization
Introduction
One dimensional optimization (Methods: Newton, golden-section search, etc.).
Multidimensional unconstrained and constrained optimization (Methods: gradient, random search, Hooke-Jeeves, etc.).
Optimization and curve fitting by least squares.
Introduction to multiobjective optimization

 

Learning Outcomes

A) solving problems by using/changing numerical methods and/or existing tools
B) knowledge of the algorithms and numerical methods studied;
C) know how to select and apply the numerical methods studied for solving ODE;
D) know how to select and apply the numerical methods studied for solving optimization problems;
E) know how to do make changes in programming codes in order to solve problems;