Thursday, 13.30 - 14.15, HFB|C
Looking at network flow problems from a combinatorial point of view the flow is typically assumed to be constant in time and flows without additional requirements such as pressure differences. This is no longer true if we look at energy networks such as water or gas networks. To appropriately model the physics of these flows partial or at least ordinary differential equations are necessary resulting even in simplified settings in non-linear non-convex constraints. In this talk we look into the details of such models, motivate them by problems showing up in the transmission of the energy system and present first solution approaches with many hints to future challenges.
Alexander Martin studied Mathematics and Economics at the University of Augsburg. He finished his PhD and habilitation theses at the Technische Universität Berlin and was debuty head of the optimization group at the Zuse Institute in Berlin. From 2000 to 2010 he became professor for discrete optimization at the Technische Universität Darmstadt, where he has been vice president from 2008 to 2010. Ever since he heads the chair on "Economics, Discrete Optimization, Mathematics (EDOM)“ at the University of Erlangen-Nuremberg.
He has been member of two cooperate research centers, the graduate school of excellence Computational Engineering and several networks supported by German ministries (BMBF and BMWi) and is currently the speaker of the cooperate research center "Mathematical Modeling, Simulation and Optimization using the Example of Gas Networks“. Besides his editorial activities for several international journals he was managing editor for the journal "Mathematical Methods of Operations Research“.
He also received honoury appointments to the BMBF advisory board "Mathematics“. His research areas are the study and solution of general mixed-integer linear and nonlinear optimization problems comprising the development of appropriate models, their analysis as well as the design and implementation of fast algorithms for their solution. The applications result from the engineering sciences and industry including network design, transportation problems and energy optimization.