3rd Porto Meeting on
MATHEMATICS for INDUSTRY 28th to 30th April 2011
MATHEMATICS for INDUSTRY 28th to 30th April 2011
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Main Speakers and courses
- Linda Allen, Department of Mathematics and Statistics, Texas Tech University USA >>> +info
Title: Mathematical
Modeling of Infectious Diseases
Abstract: Treatment methodologies, population growth, agricultural practices, and human encroachment are some of the factors that have contributed to a resurgence of old and emergence of new infectious diseases among humans, wildlife, and domestic animals. Mathematical models and methods have become increasingly important tools in the study of these emerging infectious diseases. Mathematical modeling approaches have increased our understanding of the dynamics of infectious diseases, helped interpret epidemiological trends, and provided guidelines for disease control and prevention. The basic reproduction number and herd immunity are just two concepts defined by mathematical models that are especially important in designing control programs. These concepts and others, derived from deterministic and stochastic models of infectious diseases, will be discussed in relation to vaccination programs, the development of drug resistance after treatment, and the spread of disease among animal populations. Applications will be given to measles, chickenpox, in uenza, and hantavirus.
Abstract: Treatment methodologies, population growth, agricultural practices, and human encroachment are some of the factors that have contributed to a resurgence of old and emergence of new infectious diseases among humans, wildlife, and domestic animals. Mathematical models and methods have become increasingly important tools in the study of these emerging infectious diseases. Mathematical modeling approaches have increased our understanding of the dynamics of infectious diseases, helped interpret epidemiological trends, and provided guidelines for disease control and prevention. The basic reproduction number and herd immunity are just two concepts defined by mathematical models that are especially important in designing control programs. These concepts and others, derived from deterministic and stochastic models of infectious diseases, will be discussed in relation to vaccination programs, the development of drug resistance after treatment, and the spread of disease among animal populations. Applications will be given to measles, chickenpox, in uenza, and hantavirus.
- Eligius Hendrix, Contracted Researcher Ramón y Cajal, Department of Computer Architecture, Málaga University, Associate professor Operations Research, LDI group, Wageningen University, Netherlands >>> +info
Title: Mathematical
Optimization
Applied
Abstract: Textbooks on optimization methods usually focus on how to obtain solutions of specifically structured optimization models. Analysing practical design and decision problems with the aid of optimization models requires an intuition of choice of model paradigm and feeling for difficulty of solving. We highlight the interaction between thinking about optimization technique and formulating models using three paradigms. First focus is on nonlinear programming and global optimisation. When is a problem difficult to solve? The question is discussed with models originating from 20 years of consultation work. The second topic focuses on dynamic programming. Usually this technique is seen as difficult and in our experience it requires not only long study to get a good feeling for it, but it also requires developing computer implementations or fundamental analysis to obtain adequate answers. As we will discuss, it is an elegant way to look at many practical problems. As a third modelling environment we focus on is mixed-integer linear programming. This is a more common modelling paradigm as standard software is available. We use several cases from logistics, land use planning and network analysis to give feeling.
Abstract: Textbooks on optimization methods usually focus on how to obtain solutions of specifically structured optimization models. Analysing practical design and decision problems with the aid of optimization models requires an intuition of choice of model paradigm and feeling for difficulty of solving. We highlight the interaction between thinking about optimization technique and formulating models using three paradigms. First focus is on nonlinear programming and global optimisation. When is a problem difficult to solve? The question is discussed with models originating from 20 years of consultation work. The second topic focuses on dynamic programming. Usually this technique is seen as difficult and in our experience it requires not only long study to get a good feeling for it, but it also requires developing computer implementations or fundamental analysis to obtain adequate answers. As we will discuss, it is an elegant way to look at many practical problems. As a third modelling environment we focus on is mixed-integer linear programming. This is a more common modelling paradigm as standard software is available. We use several cases from logistics, land use planning and network analysis to give feeling.
- Rosario
Mantegna, Dipartimento
di Fisica, Universita' di Palermo, Italy>>> +info
Title: Analysis and
modeling of financial markets: The approach of Econophysics
Abstract: In the last 20 years a group of physicists started describing and modeling financial markets with tools and concepts of statistical physics. In these lectures I will first present main statistical regularities empirically observed in the pricing and trading dynamics of financial assets both at the univariate and multivariate level. I will then discuss methods originating from random matrix theory, hierarchical clustering and network theory to detect economic and financial information, which is present in the multivariate dynamics of financial asset returns. I will conclude my lectures by discussing the approach of agent-based modeling of complex systems and, in particular, of the modeling of price dynamics of financial markets.
Abstract: In the last 20 years a group of physicists started describing and modeling financial markets with tools and concepts of statistical physics. In these lectures I will first present main statistical regularities empirically observed in the pricing and trading dynamics of financial assets both at the univariate and multivariate level. I will then discuss methods originating from random matrix theory, hierarchical clustering and network theory to detect economic and financial information, which is present in the multivariate dynamics of financial asset returns. I will conclude my lectures by discussing the approach of agent-based modeling of complex systems and, in particular, of the modeling of price dynamics of financial markets.
- Mattias Wahde, Department of Applied Mechanics, Chalmers University of Technology, Sweden >>> +info
Abstract:
TBAThe last decades have seen the rise of optimization methods inspired
by biological phenomena,
such as darwinian evolution, swarming, cooperation etc.
In this course, I will give an introduction to
such methods, with emphasis on practical applications.
The first topic will be a general introduction to
different biologically inspired optimization methods,
in which I will describe the various optimization
methods as well as their biological backgrounds.
The second topic will be applications of such
methods; here, a variety of examples, taken from
different fields such as robotics, vehicle dynamics,
astrophysics etc. will be considered.