@article{CombettesPokutta2023, author = {Combettes, Cyrille and Pokutta, Sebastian}, title = {Revisiting the Approximate Carath{\´e}odory Problem via the Frank-Wolfe Algorithm}, volume = {197}, journal = {Mathematical Programming A}, doi = {10.1007/s10107-021-01735-x}, pages = {191 -- 214}, year = {2023}, language = {en} } @article{Sperber2023, author = {Sperber, Wolfram}, title = {Mathematische Gesellschaft der DDR - die Vorgeschichte}, volume = {70}, journal = {Mathematische Semesterberichte}, number = {2}, publisher = {Springer Science and Business Media LLC}, issn = {0720-728X}, doi = {10.1007/s00591-023-00350-5}, pages = {103 -- 146}, year = {2023}, abstract = {ZusammenfassungDie Mathematische Gesellschaft der DDR (MGDDR) ist seit 1991 Geschichte. Die MGDDR spaltete sich 1962 auf Betreiben der Sozialistischen Einheitspartei (SED) der DDR von der Deutschen Mathematiker-Vereinigung (DMV) ab und beschloss 1990 den Zusammenschluss mit der DMV. Die Geschichte der MGDDR ist spannend, angefangen von der Vorgeschichte, ihren Aktivit{\"a}ten in der DDR-Zeit bis zur Neupositionierung nach der Wende. Und die MGDDR hat ihre Spuren in der DMV hinterlassen. Etliche Ans{\"a}tze und Aktivit{\"a}ten der MGDDR wurden von der DMV fortgef{\"u}hrt und weiterentwickelt. Aus der Literatur sind bisher nur Darstellungen einzelner Aspekte der MGDDR bekannt. Dieser Artikel unternimmt den Versuch einer Gesamtdarstellung der Geschichte der MGDDR und soll die Ausf{\"u}hrungen in [1] und [2] erg{\"a}nzen und erweitern. Die MGDDR war ein Ergebnis des Kalten Krieges und - wesentlich st{\"a}rker als bisher der {\"O}ffentlichkeit bekannt - ein Produkt der Wissenschaftspolitik von Partei und Staat der DDR. Der politische Einfluss wird in diesem Artikel durch Unterlagen belegt, die in verschiedenen Archiven gefunden wurden. Von besonderer Bedeutung bei der Recherche war das Archivgut der Stiftung Archiv der Parteien und Massenorganisationen der DDR im Bundesarchiv(SAPMO), wo seit 1990 die Unterlagen der SED, staatlicher Stellen und Massenorganisatioen der DDR systematisch aufbereitet und verf{\"u}gbar gemacht worden sind. Die Mathematiker der DDR standen der Vereinnahmung durch Partei und Staat mehrheitlich kritisch gegen{\"u}ber. Dies gilt insbesondere f{\"u}r die Zeit vor dem Mauerbau. Nach dem Mauerbau und den Einschr{\"a}nkungen des Reiseverkehrs war f{\"u}r die meisten Mathematiker der DDR die Gr{\"u}ndung einer eigenen Fachgesellschaft alternativlos. Diese erfolgte am 8. Juni 1962. Nach dem Mauerbau war f{\"u}r die Mathematiker in der DDR wissenschaftlicher Austausch ohne Einbeziehung der MGDDR nahezu unm{\"o}glich. F{\"u}r die Arbeit der MGDDR standen aber immer mathematische Ziele im Zentrum und die MGDDR war dabei - trotz einiger Behinderungen - durchaus erfolgreich. Nach der Wende positionierte sich die MGDDR neu und beschloss auf dem Mathematiker-Kongress der DDR im September 1990 den Zusammenschluss mit der DMV. Der vorliegende Artikel umfasst die Vorgeschichte der MGDDR bis zu deren Gr{\"u}ndung am 08.06.1962. In zwei weiteren Publikationen soll die Arbeit der MGDDR bis zur Wende und dem Zusammenschluss mit der DMV dargestellt werden.}, language = {de} } @article{AndresArconesWeiserKoutsourelakisetal.2023, author = {Andr{\´e}s Arcones, Daniel and Weiser, Martin and Koutsourelakis, Faidon-Stelios and Unger, J{\"o}rg F.}, title = {A Bayesian Framework for Simulation-based Digital Twins of Bridges}, volume = {6}, journal = {EUROSTRUCT 2023:European Association on Quality Control of Bridges and Structures: Digital Transformation in Sustainability}, number = {5}, doi = {10.1002/cepa.2177}, pages = {734 -- 740}, year = {2023}, abstract = {Simulation-based digital twins have emerged as a powerful tool for evaluating the mechanical response of bridges. As virtual representations of physical systems, digital twins can provide a wealth of information that complements traditional inspection and monitoring data. By incorporating virtual sensors and predictive maintenance strategies, they have the potential to improve our understanding of the behavior and performance of bridges over time. However, as bridges age and undergo regular loading and extreme events, their structural characteristics change, often differing from the predictions of their initial design. Digital twins must be continuously adapted to reflect these changes. In this article, we present a Bayesian framework for updating simulation-based digital twins in the context of bridges. Our approach integrates information from measurements to account for inaccuracies in the simulation model and quantify uncertainties. Through its implementation and assessment, this work demonstrates the potential for digital twins to provide a reliable and up-to-date representation of bridge behavior, helping to inform decision-making for maintenance and management.}, language = {en} } @article{GuptaHamannMueyesseretal.2023, author = {Gupta, Pranshu and Hamann, Fabian and M{\"u}yesser, Alp and Sgueglia, Amedeo and Parczyk, Olaf}, title = {A general approach to transversal versions of Dirac-type theorems}, volume = {55}, journal = {Bulletin of the London Mathematical Society}, number = {6}, pages = {2817 -- 2839}, year = {2023}, language = {en} } @article{KohayakawaMotaSchnitzeretal.2023, author = {Kohayakawa, Yoshiharu and Mota, Guilherme O. and Schnitzer, Jakob and Parczyk, Olaf}, title = {Anti-Ramsey threshold of complete graphs for sparse graphs}, journal = {Discrete Mathematics}, year = {2023}, language = {en} } @article{SchemberaWuebbelingKopruckietal.2023, author = {Schembera, Bj{\"o}rn and W{\"u}bbeling, Frank and Koprucki, Thomas and Biedinger, Christine and Reidelbach, Marco and Schmidt, Burkhard and G{\"o}ddeke, Dominik and Fiedler, Jochen}, title = {Building Ontologies and Knowledge Graphs for Mathematics and its Applications}, volume = {1}, journal = {Proceedings of the Conference on Research Data Infrastructure}, publisher = {TIB Open Publishing}, issn = {2941-296X}, doi = {10.52825/cordi.v1i.255}, year = {2023}, abstract = {Ontologies and knowledge graphs for mathematical algorithms and models are presented, that have been developed by the Mathematical Research Data Initiative. This enables FAIR data handling in mathematics and the applied disciplines. Moreover, challenges of harmonization during the ontology development are discussed.}, language = {en} } @article{ReidelbachFerrerWeber2023, author = {Reidelbach, Marco and Ferrer, Eloi and Weber, Marcus}, title = {MaRDMO Plugin}, volume = {1}, journal = {Proceedings of the Conference on Research Data Infrastructure}, publisher = {TIB Open Publishing}, issn = {2941-296X}, doi = {10.52825/cordi.v1i.254}, year = {2023}, abstract = {MaRDMO, a plugin for the Research Data Management Organiser, was developed in the Mathematical Research Data Initiative to document interdisciplinary workflows using a standardised scheme. Interdisciplinary workflows recorded this way are published directly on the MaRDI portal. In addition, central information is integrated into the MaRDI knowledge graph. Next to the documentation, MaRDMO offers the possibility to retrieve existing interdisciplinary workflows from the MaRDI Knowledge Graph to allow the reproduction of the initial work and to provide scientists with new researchimpulses. Thus, MaRDMO creates a community-driven knowledge loop that could help to overcome the replication crisis.}, language = {en} } @article{BennerDanabalanGoedekkeetal.2023, author = {Benner, Peter and Danabalan, Renita and G{\"o}dekke, Dominik and Kastner, Lars and Krause, Tabea and Mietchen, Daniel and Reidelbach, Marco and Schembera, Bj{\"o}rn and Schubotz, Moritz and Sinn, Rainer and Tabelow, Karsten}, title = {Research Data Management Planning in Mathematics}, doi = {10.5281/zenodo.10018245}, year = {2023}, abstract = {Research data are crucial in mathematics and all scientific disciplines, as they form the foundation for empirical evidence, by enabling the validation and reproducibility of scientific findings. Mathematical research data (MathRD) have become vast and complex, and their interdisciplinary potential and abstract nature make them ubiquitous in various scientific fields. The volume of data and the velocity of its creation are rapidly increasing due to advancements in data science and computing power. This complexity extends to other disciplines, resulting in diverse research data and computational models. Thus, proper handling of research data is crucial both within mathematics and for its manifold connections and exchange with other disciplines. The National Research Data Infrastructure (NFDI), funded by the federal and state governments of Germany, consists of discipline-oriented consortia, including the Mathematical Research Data Initiative (MaRDI). MaRDI has been established to develop services, guidelines and outreach measures for all aspects of MathRD, and thus support the mathematical research community. Research data management (RDM) should be an integral component of every scientific project, and is becoming a mandatory component of grants with funding bodies such as the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation). At the core of RDM are the FAIR (Findable, Accessible, Interoperable, and Reusable) principles. This document aims to guide mathematicians and researchers from related disciplines who create RDM plans. It highlights the benefits and opportunities of RDM in mathematics and interdisciplinary studies, showcases examples of diverse MathRD, and suggests technical solutions that meet the requirements of funding agencies with specific examples. The document is regularly updated to reflect the latest developments within the mathematical community represented by MaRDI.}, language = {en} } @article{Winkler2023, author = {Winkler, Alexander}, title = {Berliner Kulturerbe digital: Ein quantitativer Blick auf die Metadatenqualit{\"a}t}, journal = {EVA BERLIN 2023. Elektronische Medien \& Kunst, Kultur und Historie. 27. Berliner Veranstaltung der internationalen EVA-Serie (29. November 2023 - 01. Dezember 2023)}, pages = {101 -- 108}, year = {2023}, abstract = {Die Metadatenqualit{\"a}t bestimmt wesentlich den Nutzen und Wert von Kulturerbedaten. ‚Gute' Metadaten erh{\"o}hen die Auffindbarkeit, Interoperabilit{\"a}t und Nutzbarkeit von Daten signifikant. Mit Blick auf Retrieval bzw. Discovery, Vernetzung im Kontext von Linked Open Data und wissenschaftliches Data Mining h{\"a}ngt die Qualit{\"a}t dabei wesentlich von der Verwendung von maschinenlesbaren kontrollierten Vokabularen ab. Diese wird in der vorliegenden Arbeit quantitativ untersucht. Als Datengrundlage dienen die in der Deutschen Digitalen Bibliothek aggregierten Metadaten aus Berliner Museen (ca. 1,2 Millionen Metadatenobjekte im LIDO-Format)}, language = {de} } @article{BreugemSchlechteSchulzetal.2023, author = {Breugem, Thomas and Schlechte, Thomas and Schulz, Christof and Bornd{\"o}rfer, Ralf}, title = {A three-phase heuristic for the Fairness-Oriented Crew Rostering Problem}, volume = {154}, journal = {Computers \& Operations Research}, doi = {10.1016/j.cor.2023.106186}, pages = {106186}, year = {2023}, abstract = {The Fairness-Oriented Crew Rostering Problem (FCRP) considers the joint optimization of attractiveness and fairness in cyclic crew rostering. Like many problems in scheduling and logistics, the combinatorial complexity of cyclic rostering causes exact methods to fail for large-scale practical instances. In case of the FCRP, this is accentuated by the additionally imposed fairness requirements. Hence, heuristic methods are necessary. We present a three-phase heuristic for the FCRP combining column generation techniques with variable-depth neighborhood search. The heuristic exploits different mathematical formulations to find feasible solutions and to search for improvements. We apply our methodology to practical instances from Netherlands Railways (NS), the main passenger railway operator in the Netherlands Our results show the three-phase heuristic finds good solutions for most instances and outperforms a state-of-the-art commercial solver.}, language = {en} }