Prof. Dr. Stefan Voß (Univ. Hamburg) | 30.1.2020 15:00 | HS3 OMP1


Network based systems are at the core of our every-day life. Whether it is electronic networking, electricity grids or transportation, we expect the networks to function properly and give us a feeling of safety and security. However, there may be disturbances. In this presentation, we consider disturbances in the context of public transportation and maritime shipping. To classify and cope with disturbances, we find many words in literature that often are more or less loosely coupled, including robustness, resilience, vulnerability, disruption mitigation or delay management, just to mention a few. We survey related literature and put them into perspective. As a major insight we show that different strands of literature exist that may benefit from becoming better connected and intertwined.

Kurt Anstreicher (Univ. Iowa) | 27.1.2020 16:45-17:45 | HS7 OMP1


The maximum-entropy sampling problem (MESP) is a difficult nonlinear integer programming problem that arises in spatial statistics, for example in the design of weather monitoring networks. We describe a new bound for the MESP that is based maximizing a function of the form ldet M(x) over linear constraints, where M(x) is an n-by-n matrix function that is linear in the n-vector x. These bounds can be computed very efficiently and are superior to all previously known bounds for MESP on most benchmark test problems. A branch-and-bound algorithm using the new bounds solves challenging instances of MESP to optimality for the first time.