@inproceedings{48879, abstract = {{Evolving diverse sets of high quality solutions has gained increasing interest in the evolutionary computation literature in recent years. With this paper, we contribute to this area of research by examining evolutionary diversity optimisation approaches for the classical Traveling Salesperson Problem (TSP). We study the impact of using different diversity measures for a given set of tours and the ability of evolutionary algorithms to obtain a diverse set of high quality solutions when adopting these measures. Our studies show that a large variety of diverse high quality tours can be achieved by using our approaches. Furthermore, we compare our approaches in terms of theoretical properties and the final set of tours obtained by the evolutionary diversity optimisation algorithm.}}, author = {{Do, Anh Viet and Bossek, Jakob and Neumann, Aneta and Neumann, Frank}}, booktitle = {{Proceedings of the Genetic and Evolutionary Computation Conference}}, isbn = {{978-1-4503-7128-5}}, keywords = {{diversity maximisation, evolutionary algorithms, travelling salesperson problem}}, pages = {{681–689}}, publisher = {{Association for Computing Machinery}}, title = {{{Evolving Diverse Sets of Tours for the Travelling Salesperson Problem}}}, doi = {{10.1145/3377930.3389844}}, year = {{2020}}, } @inproceedings{48895, abstract = {{Evolutionary algorithms (EAs) are general-purpose problem solvers that usually perform an unbiased search. This is reasonable and desirable in a black-box scenario. For combinatorial optimization problems, often more knowledge about the structure of optimal solutions is given, which can be leveraged by means of biased search operators. We consider the Minimum Spanning Tree (MST) problem in a single- and multi-objective version, and introduce a biased mutation, which puts more emphasis on the selection of edges of low rank in terms of low domination number. We present example graphs where the biased mutation can significantly speed up the expected runtime until (Pareto-)optimal solutions are found. On the other hand, we demonstrate that bias can lead to exponential runtime if "heavy" edges are necessarily part of an optimal solution. However, on general graphs in the single-objective setting, we show that a combined mutation operator which decides for unbiased or biased edge selection in each step with equal probability exhibits a polynomial upper bound - as unbiased mutation - in the worst case and benefits from bias if the circumstances are favorable.}}, author = {{Roostapour, Vahid and Bossek, Jakob and Neumann, Frank}}, booktitle = {{Proceedings of the 2020 Genetic and Evolutionary Computation Conference}}, isbn = {{978-1-4503-7128-5}}, keywords = {{biased mutation, evolutionary algorithms, minimum spanning tree problem, runtime analysis}}, pages = {{551–559}}, publisher = {{Association for Computing Machinery}}, title = {{{Runtime Analysis of Evolutionary Algorithms with Biased Mutation for the Multi-Objective Minimum Spanning Tree Problem}}}, doi = {{10.1145/3377930.3390168}}, year = {{2020}}, } @inproceedings{48897, abstract = {{In this work we focus on the well-known Euclidean Traveling Salesperson Problem (TSP) and two highly competitive inexact heuristic TSP solvers, EAX and LKH, in the context of per-instance algorithm selection (AS). We evolve instances with nodes where the solvers show strongly different performance profiles. These instances serve as a basis for an exploratory study on the identification of well-discriminating problem characteristics (features). Our results in a nutshell: we show that even though (1) promising features exist, (2) these are in line with previous results from the literature, and (3) models trained with these features are more accurate than models adopting sophisticated feature selection methods, the advantage is not close to the virtual best solver in terms of penalized average runtime and so is the performance gain over the single best solver. However, we show that a feature-free deep neural network based approach solely based on visual representation of the instances already matches classical AS model results and thus shows huge potential for future studies.}}, author = {{Seiler, Moritz and Pohl, Janina and Bossek, Jakob and Kerschke, Pascal and Trautmann, Heike}}, booktitle = {{Parallel Problem Solving from {Nature} (PPSN XVI)}}, isbn = {{978-3-030-58111-4}}, keywords = {{Automated algorithm selection, Deep learning, Feature-based approaches, Traveling Salesperson Problem}}, pages = {{48–64}}, publisher = {{Springer-Verlag}}, title = {{{Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem}}}, doi = {{10.1007/978-3-030-58112-1_4}}, year = {{2020}}, } @article{48848, abstract = {{We build upon a recently proposed multi-objective view onto performance measurement of single-objective stochastic solvers. The trade-off between the fraction of failed runs and the mean runtime of successful runs \textendash both to be minimized \textendash is directly analyzed based on a study on algorithm selection of inexact state-of-the-art solvers for the famous Traveling Salesperson Problem (TSP). Moreover, we adopt the hypervolume indicator (HV) commonly used in multi-objective optimization for simultaneously assessing both conflicting objectives and investigate relations to commonly used performance indicators, both theoretically and empirically. Next to Penalized Average Runtime (PAR) and Penalized Quantile Runtime (PQR), the HV measure is used as a core concept within the construction of per-instance algorithm selection models offering interesting insights into complementary behavior of inexact TSP solvers. \textbullet The multi-objective perspective is naturally generalizable to multiple objectives. \textbullet Proof of relationship between HV and the PAR in the considered bi-objective space. \textbullet New insights into complementary behavior of stochastic optimization algorithms.}}, author = {{Bossek, Jakob and Kerschke, Pascal and Trautmann, Heike}}, issn = {{1568-4946}}, journal = {{Applied Soft Computing}}, keywords = {{Algorithm selection, Combinatorial optimization, Multi-objective optimization, Performance measurement, Traveling Salesperson Problem}}, number = {{C}}, title = {{{A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms}}}, doi = {{10.1016/j.asoc.2019.105901}}, volume = {{88}}, year = {{2020}}, } @article{48836, author = {{Bartz-Beielstein, Thomas and Doerr, Carola and van den Berg, Daan and Bossek, Jakob and Chandrasekaran, Sowmya and Eftimov, Tome and Fischbach, Andreas and Kerschke, Pascal and Cava, William La and Lopez-Ibanez, Manuel and Malan, Katherine M. and Moore, Jason H. and Naujoks, Boris and Orzechowski, Patryk and Volz, Vanessa and Wagner, Markus and Weise, Thomas}}, journal = {{Corr}}, title = {{{Benchmarking in Optimization: Best Practice and Open Issues}}}, year = {{2020}}, } @misc{49599, author = {{Fastlabend-Vargas, Daniel}}, publisher = {{Zwischentöne.info }}, title = {{{Geschichte(n) der deutschen Migrationsgesellschaft. Jugendliche erzählen begründete historische Geschichten Eine Unterrichtsreihe für das Portal Zwischentöne.info }}}, year = {{2020}}, } @book{30869, author = {{Lammer, Christina}}, publisher = {{transcript Verlag}}, title = {{{Erinnerung und Identität: Literarische Konstruktionen in Doeschka Meijsings Prosa}}}, year = {{2020}}, } @misc{49767, author = {{Huybrechts, Yves}}, publisher = {{BelgienNet}}, title = {{{"Die Bombardierung von Brüssel - teil 1" (PODCAST)}}}, year = {{2020}}, } @article{49736, author = {{Huybrechts, Yves}}, isbn = {{9783451032967}}, issn = {{00182621}}, journal = {{Historisches Jahrbuch}}, pages = {{420--445}}, title = {{{Den Kaiser erpressen. Der Fall Jever zwischen Burgundischem Reichskreis und Reichskammergericht, 1737-1739}}}, volume = {{140}}, year = {{2020}}, } @misc{49756, author = {{Huybrechts, Yves}}, publisher = {{BelgienNet}}, title = {{{"Ein Gespräch mit Guy Vanhengel - Ein Gespräch mit dem Vizepräsidenten des Brüsseler Parlaments, in zwei Teilen." (VIDEO)}}}, year = {{2020}}, } @misc{49750, author = {{Huybrechts, Yves}}, publisher = {{BelgienNet}}, title = {{{Interview zur Ausstellung "Rubens und der Barock im Norden" - 2 Teile (VIDEO)}}}, year = {{2020}}, } @inbook{49831, author = {{Diedrich, Alena}}, booktitle = {{Forcierte Form: Deutschsprachige Versepik des 20. und 21. Jahrhunderts im europäischen Kontext}}, editor = {{Bremer, Kai and Elit, Stefan and Kroucheva, Katerina}}, publisher = {{Metzler}}, title = {{{Ironie als forcierte Form. Hans Magnus Enzensbergers Versepos Der Untergang der Titanic}}}, year = {{2020}}, } @inbook{49832, author = {{Diedrich, Alena}}, booktitle = {{Handbuch Vormärz}}, editor = {{Eke, Norbert Otto }}, publisher = {{Aisthesis}}, title = {{{Lyrik im Vormärz}}}, year = {{2020}}, } @inbook{49833, author = {{Diedrich, Alena}}, booktitle = {{Handbuch Vormärz}}, editor = {{Eke, Norbert Otto }}, publisher = {{Aisthesis}}, title = {{{Nikolaus Lenau}}}, year = {{2020}}, } @inbook{49869, author = {{Neiske, Iris and Bücker, Diana}}, booktitle = {{Medienpädagogik als Schlüsseldisziplin in einer mediatisierten Welt. Perspektiven aus Theorie, Empirie und Praxis 37}}, issn = {{1424-3636}}, pages = {{299--312}}, title = {{{Medienpädagogik und Hochschuldidaktik}}}, year = {{2020}}, } @book{49915, editor = {{Autsch, Sabiene and Pickartz, Tim}}, title = {{{Impulse 5. Texte und Bilder zur Kunstvermittlung: Go West! Kunst- und Ausstellungsszene New York 2019.}}}, year = {{2020}}, } @book{49917, editor = {{Autsch, Sabiene}}, title = {{{"Was machst du gerade?" Essays aus dem Atelier in Zeiten von Corona}}}, year = {{2020}}, } @misc{49947, author = {{Autsch, Sabiene}}, booktitle = {{PUR [= Paderborner Universitätsreden. Hg. von. Prof. em. Dr. Dr. hc. malt. Peter Freese]}}, number = {{155}}, pages = {{18--22}}, title = {{{Festrede auf Maria v. Welser anlässlich der Verleihung der Ehrendoktorwürde am 14.11.2019 durch die kulturwissenschaftliche Fakultät der Universität Paderborn}}}, year = {{2020}}, } @article{50105, author = {{Pauls, Karina}}, journal = {{Kunst+Unterricht 441/442}}, pages = {{S. 12--17}}, title = {{{Alice im Wunderland. Ein Klassiker der Kinderliteratur als Künstlerbuch}}}, year = {{2020}}, } @inbook{50137, author = {{Dahmen, Stephan and Bonvin, Jean-Michel}}, booktitle = {{Wörterbuch der Schweizer Sozialpolitik}}, editor = {{Knöpfel, Carlo and Maeder, Pascal and Tecklenburg, Ueli}}, publisher = {{Seismo Verlag}}, title = {{{Soziale Investition}}}, doi = {{doi.org/10.33058/seismo.30739}}, year = {{2020}}, }