Symbolic and Algebraic Computation for Optimization Tasks in Science and Engineering
Ernst W. Mayr
für Effiziente Algorithmen
Institut für Informatik
Technische Universität München
Various applications in robotics, manufacturing, molecular biology, nanotechnology, etc. involve optimization and optimal control with constraints given by algebraic and differential equations (both ODEs and PDEs). Especially in the case of differential constraints, the "naive" approaches combining numerical solvers for differential equations and optimization algorithms may lead to lack of robustness or be very inefficient.
In order to deal with real life applications stability and fast convergence of numerical methods have to be provided. However, research in this field is very much in progress, and many problems concerning both the theoretical foundations and practical issues remain open: existence of optimizers for underlying continuous problem and necessary optimality conditions, questions of stability and convergence for numerical methods, the interplay between discretization and optimization, etc.
These issues require a wide range of mathematical disciplines (e.g. optimal control theory, functional analysis, numerical analysis, etc.) as well as engineering understanding in order to choose the appropriate mathematical model for the problem at hand. The goal of this session is to bring together mathematicians and engineers, who develop or use algebraic and numerical methods, to exchange ideas and views, and to present both original research results involving computer algebra as well as challenging directions and industrial applications.
Possible topics for this session include (but are not limited to):
to Dmytro Chibisov, Victor Ganzha, and Ernst Mayr by June 6.