Plenary lecture VI: new trends in multivariate approximation and optimization
Dana Simian · 2008
Multivariate approximation and optimization appear in modeling real systems. The aim of this lecture is to present new algorithms and computational techniques for solving practical problems of approximation an optimization and to make a comparison between them. In the first part, genetic algorithms, ant and wasp behaviour algorithms are taking into account and applied to agent-based approaches to manufacturing scheduling and control in distributed manufacturing systems and to adaptive multiagent systems. In the second part we present new results in multivariate interpolation and polyspline and their applications in image processing and classification theory. A reformulation of the problem of multivariate interpolation which allows the use of methods taken from artificial intelligence make a connection between the two parts of the presentation. As a conclusion, problems from many other fields, like chemistry, biology, medicine which can be solve using the presented algorithms and techniques are presented.