Data is often thought of as the resource of the future. The enormous amount of data that is currently available leads to new scientific and economic questions, such as: “How can companies extract useful information from the available data to support their business processes,“ or “How can analysis of the available data improve medical diagnostics?“ The field of research that concerns itself with such questions is called ‘”Analytics” and can be divided into the following areas:

  • Descriptive Analytics (“What is the current state?”)
  • Predictive Analytics (“What developments are most likely?”)
  • Prescriptive Analytics (“What should we do?”)

At present “Analytics” combined with buzzwords like “Big Data”, “Internet of Things” or “Smart Data” is a widely discussed topic in the scientific world as well as in business. However, most of the discussions focus just on the first two of the above mentioned subfields: How can we gather this data? How can we recognize its essential characteristics? How will it evolve in the future? Yet the underrepresented third subject is the one with the biggest potential: How can we use this data to assist us in decision making and how can we choose among different alternatives in order to optimize processes or even identify completely new business segments or develop new business models. In other words, what better ways are there to make use of data in mathematical optimization? In our working group we address exactly this question. The following projects provide further insight into our work on this topic.

Ongoing Projects

ADA Lovelace Center for Analytics, Data and Applications

The ADA Lovelace Center for Analytics, Data and Applications is a competence center for artificial intelligence. It was founded by the Fraunhofer Institute for Integrated Circuits (IIS), Friedrich-Alexander-Universität Erlangen-Nürnberg (IIS) and Ludwig-Maximilians-Universität München (LMU).

Optimal Control of Electrical Distribution Networks with Uncertain Solar Feed-In

The objective of this project is to develop innovative techniques for modelling, simulation and optimization of electrical distribution networks with regard to uncertain solar feed-in. We want to study and optimize fluctuating energy feed and corresponding power flows. Therefore new mathematical approaches will be combined to guarantee a efficient design and stable real-time operation.
Participants: Frauke Liers, Alexander Martin, Kevin-Martin Aigner

Optimization of medical care in rural environments

Ambulatory care is an essential part of our health care system. This system faces major challenges, especially with respect to demographic changes, centralization of health care facilities as well as a combination of dwindling ressources and increasing costs. This change is already noticeable in rural environments. Small villages and dispersed settlements are affected by huge population decreases. Hence, the current medical infrastructure is no longer sustainable.
Participants: Frauke Liers, Sebastian Tschuppik

EWave – Water Supply Energy Management System

Over the past few years, requirements for drinking water supply in Germany have become more and more demanding. While the secure supply of high-quality drinking water for the public was the priority during the past decades, rising energy costs and the energy reform being implemented by the German Federal Government now also require that energy is used efficiently. The joint research project EWave aims to develop an innovative energy management system. The objective is to devise energy-optimized operating plans for plants for water collection, treatment, and distribution within the supply system by using state-of-the-art methods, algorithms and software from discrete and continuous optimization.
Participants: Alexander Martin, Björn Geißler, Antonio Morsi

Finished Projects

Robust Power Load Balancing in Railway Networks

The aim of this project are robust train schedules with respect to the power consumption from the power supply stations. The input is a given schedule which is slightly adapted to desynchronize simultaneous train departures. On the other hand, train departures are synchronized with the recuperation phases of other trains to make use of their braking energy. Preliminary results show that significant savings with respect to the provision of reserve power can be achieved.
Participants: Andreas Bärmann

Optimization of Hybrid Energy Systems

Hybrid energy systems usually consist of two or more energy sources with at least one renewable source and one completely controllable source. In our case the hybrid system also comprises of energy storages, different types of energy consumers and a mini-grid connecting a small number of households. The aim of the project is the optimization of the internal and external power distribution, i. e. inside the individual households as well as between the different households, in order to minimize the energy costs while satisfying the demands.
Participants: Katja Kutzer, Björn Geißler

LeOpIn – Life-cycle oriented optimization for a resource- and energy-efficient infrastructure

The goal of the project LeOpIn is to devise methods for life-cycle oriented planning and evaluation of buildings and related infrastructure. To this end we develop simulation and optimization tools which can cope with this task. A concrete application is the planning of a building and pipes undergoing high pressure scenarios for which a software solution will be prototypically developed. The development of the planning and evaluation procedures demands a tight interaction between mathematical and engineering techniques. We plan to employ methods of numerical simulation and of discrete and nonlinear optimization. The main focus lies on integration of these techniques since only by this the high complexity of the treated problems can be handled appropriately.
Participants: Alexander Martin, Stefan Schmieder (Project A) and Lars Schewe, Jakob Schelbert (Project B)

Robust Schedules for Air Traffic Management

Increasing air traffic and new procedures in air traffic management require a very efficient use of limited ATM resources. It is impossible to create schedules for future use which never need to be adapted. Reasons are e.g., unexpected weather conditions, late passengers, and intended and unintended deviations from schedules. We tackle scheduling problems in ATM, like the planning of airplanes on runways. Therefore, the focus of the assigned task lies on modeling, understanding and controlling uncertainty in ATM problems. So it is important to concern with Resilience and Adaptation to continue having air transport and to be competitive to alternative transportation. Thus we have to accept these phenomena and have to incorporate uncertainty into the model.
Participants: Andreas Heidt

Expansion of the German Rail Freight Network

In recent years, rail freight traffic in Germany has attained a significant growth. In contrast, the expansion of the available transportation capacities in the German railway network has always dragged behind this development. The short term drop in demand due to the economic crisis offers the opportunity to make up for this deficit. The goal is to prepare the railway network for the demand growth forecasted for the upcoming years. Recent studies predict annual growth rates of 5% within the next 15 years, which would result in a freight traffic more than twice as high as nowadays. This requires extensive investments in the construction of new tracks and the expansion of existing ones.
Participants: Andreas Bärmann

RobustATM: Robust Optimization of ATM Planning Processes by Modelling of Uncertainty Impact

As possibilities of enlarging airport capacities are limited, one has to enhance the utilization of existing capacities in Air Traffic Management (ATM) to meet the continuous growth of traffic demand. Therefore, it is crucial for the performance of the whole ATM System that the traffic on a runway is planned efficiently. However, uncertainty, inaccuracy and non-determinism almost always lead to deviations from the actual plan or schedule. A typical strategy to deal with these changes is a regular re-computation or update of the schedule. These adjustments are performed in hindsight, i.e. after the actual change in the data occurred. The challenge is to incorporate uncertainty into the initial computation of the plans so that these plans are robust with respect to changes in the data, leading to a better utilization of resources.
Participants: Andreas Heidt, Manu Kapolke, Frauke Liers


Friedrich-Alexander-Universität Erlangen-Nürnberg