Press Releases

Complex optimization problems with many, in particular discrete variables are usually difficult to solve for classical computers. Only recently, certain types of quantum computers have achieved promising results in solving optimization problems. They showed the potential to handle discrete variables as well. In the joint project »EnerQuant: Fundamental modeling in energy economics with quantum algorithms«, the advantages of quantum computing are now to be used for an optimization problem in energy economics.

Billing fraud committed by contract physicians or outpatient nursing services has been the focus of investigations and media discussion in the healthcare sector for years. The Fraunhofer Institute for Industrial Mathematics ITWM supports the efficient clarification with new methods.

International networks enrich the scientific exchange. Within the framework of the European Union's THREAD doctoral program, this is currently lived out twice at the Fraunhofer ITWM: In July, the institute welcomes THREAD doctoral student Denise Tumiotto, who will spend four weeks as a guest scientist in the field of "Mathematics for Vehicle Development". In addition, the first network-wide training took place at the beginning of the month, which the 14 PhD students of the program from eight European countries completed together.

Dr. Stefanie Schwaar from the Fraunhofer Institute for Industrial Mathematics ITWM won the BMBF's call for funding young female AI researchers. She will establish and head her own research group at the mathematical institute from August 2020. Under the title »EP-KI: Decision Support for Business Management Processes with the Help of New AI Methods« they will work at the interface of business management and artificial intelligence (AI). An excellent network of administration, business and research supports the group, which is funded by the Federal Ministry of Education and Research.

The coronavirus pandemic has hit the economy hard. What lessons can be learned from this experience? And what’s the best way for companies to protect themselves against this kind of crisis in the future? The answer will certainly involve a combination of different approaches – but new mathematical methods developed by the Fraunhofer Institute for Industrial Mathematics ITWM look likely to be a very promising piece of the puzzle. These methods aim to calculate how the risks posed by supply shortages can be reduced significantly at very little extra cost.

How long can you wear a protection mask? When will you have to change a soaked mask? Researchers of the Fraunhofer ITWM tackle these question using mathematical models and computer simulations. It is important to take into account not only the type of mask and the filter material, but also the physical stress level and personal features of the wearer.

Especially when an infectious disease is new, mathematical models help to answer the two most important questions: How will the infection spread and what actions are appropriate and effective to contain it? In order to support local decision makers (health authorities, hospitals and especially municipalities) in planning their actions, researchers of the Fraunhofer ITWM are working on the epidemiological modeling, simulation and decision support of Covid-19 within the framework of the Fraunhofer Society's Anti-Corona Program (project name EpiDeMSE).

Researchers at the Fraunhofer Institute for Industrial Mathematics ITWM in Kaiserslautern are developing a prediction model for the spread of Covid-19 which, in contrast to classical models, is better able to detect "suddenly changing infection rates after actions have been taken". In addition, the researchers are simulating several spatially or age-separated groups in a network. The research work is being carried out as part of the "Fraunhofer vs. Corona" action program.

Simulations by the Fraunhofer Institute for Industrial Mathematics ITWM make processes in the manufacturing of nonwovens more efficient. Within the anti-corona program of Fraunhofer the production of infection protection is optimized.

Catalysts are commonly used to reduce pollutants released in car exhaust. In order to manufacture catalytic filters with even higher efficiency, industry is increasingly relying on innovative mathematical models and machine learning (ML). In the newly launched collaborative research project «ML-MORE», researchers at the Cluster of Excellence «Mathematics Münster» at the University of Münster are working closely with the Fraunhofer Institute for Industrial Mathematics ITWM, the University of Stuttgart, TU Darmstadt and Umicore AG & Co. KG, a materials technology and recycling company. The Federal Ministry of Education and Research (BMBF) is funding the project as part of «Mathematics for Innovations», a programme devoted to developing methods for handling large volumes of data. The BMBF has allocated approximately one million euros to finance the project over the next three years.«Mathematics for Innovations», a programme devoted to developing methods for handling large volumes of data. The BMBF has allocated approximately one million euros to finance the project over the next three years.