Inhalt:

Abstract:

Modeling, Simulation, and Optimization (MSO) is one of the cornerstones of application-oriented mathematics.

It covers a broad spectrum of research activities, ranging from the design of mathematical models for real-world processes, via efficient numerical simulation algorithms, to the solution of optimization problems for finding optimal scenarios or controls for the process under consideration. This lecture will give an overview over the techniques used in MSO and its application in different areas (life science, mobility, energy, sustainability, …). The lecture will be complemented by several pilot projects in which student groups will develop MSO solutions for realistic (but not too complex) application problems.

Zielpublikum:
Master Mathematik
 

Literatur

•  Winkelmann and Schütte (2020): Stochastic Dynamics in Computational Biology, in: Frontiers in Applied Dynamical Systems: Reviews and Tutorials, Volume 8 (Springer)
• Gardiner (2004): Stochastic methods: a handbook for the natural and social sciences (Springer)
• Riley, Hobson and Bence (2002): Mathematical Methods for Physics and Engineering (Cambridge)
• Deuflhard and Roeblitz (2015): A guide to numerical modelling in systems biology Texts in computational science and engineering, Volume 12 (Springer)