[{"series_title":"GECCO’20","language":[{"iso":"eng"}],"doi":"10.1145/3377930.3389844","author":[{"full_name":"Do, Anh Viet","first_name":"Anh Viet","last_name":"Do"},{"last_name":"Bossek","orcid":"0000-0002-4121-4668","first_name":"Jakob","full_name":"Bossek, Jakob","id":"102979"},{"last_name":"Neumann","first_name":"Aneta","full_name":"Neumann, Aneta"},{"first_name":"Frank","last_name":"Neumann","full_name":"Neumann, Frank"}],"publication_identifier":{"isbn":["978-1-4503-7128-5"]},"year":"2020","title":"Evolving Diverse Sets of Tours for the Travelling Salesperson Problem","date_updated":"2023-12-13T10:48:50Z","date_created":"2023-11-14T15:58:58Z","department":[{"_id":"819"}],"type":"conference","keyword":["diversity maximisation","evolutionary algorithms","travelling salesperson problem"],"publication":"Proceedings of the Genetic and Evolutionary Computation Conference","extern":"1","abstract":[{"text":"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.","lang":"eng"}],"_id":"48879","publisher":"Association for Computing Machinery","page":"681–689","user_id":"102979","status":"public","place":"New York, NY, USA","citation":{"ama":"Do AV, Bossek J, Neumann A, Neumann F. Evolving Diverse Sets of Tours for the Travelling Salesperson Problem. In: <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>. GECCO’20. Association for Computing Machinery; 2020:681–689. doi:<a href=\"https://doi.org/10.1145/3377930.3389844\">10.1145/3377930.3389844</a>","bibtex":"@inproceedings{Do_Bossek_Neumann_Neumann_2020, place={New York, NY, USA}, series={GECCO’20}, title={Evolving Diverse Sets of Tours for the Travelling Salesperson Problem}, DOI={<a href=\"https://doi.org/10.1145/3377930.3389844\">10.1145/3377930.3389844</a>}, booktitle={Proceedings of the Genetic and Evolutionary Computation Conference}, publisher={Association for Computing Machinery}, author={Do, Anh Viet and Bossek, Jakob and Neumann, Aneta and Neumann, Frank}, year={2020}, pages={681–689}, collection={GECCO’20} }","mla":"Do, Anh Viet, et al. “Evolving Diverse Sets of Tours for the Travelling Salesperson Problem.” <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, Association for Computing Machinery, 2020, pp. 681–689, doi:<a href=\"https://doi.org/10.1145/3377930.3389844\">10.1145/3377930.3389844</a>.","short":"A.V. Do, J. Bossek, A. Neumann, F. Neumann, in: Proceedings of the Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2020, pp. 681–689.","chicago":"Do, Anh Viet, Jakob Bossek, Aneta Neumann, and Frank Neumann. “Evolving Diverse Sets of Tours for the Travelling Salesperson Problem.” In <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, 681–689. GECCO’20. New York, NY, USA: Association for Computing Machinery, 2020. <a href=\"https://doi.org/10.1145/3377930.3389844\">https://doi.org/10.1145/3377930.3389844</a>.","apa":"Do, A. V., Bossek, J., Neumann, A., &#38; Neumann, F. (2020). Evolving Diverse Sets of Tours for the Travelling Salesperson Problem. <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, 681–689. <a href=\"https://doi.org/10.1145/3377930.3389844\">https://doi.org/10.1145/3377930.3389844</a>","ieee":"A. V. Do, J. Bossek, A. Neumann, and F. Neumann, “Evolving Diverse Sets of Tours for the Travelling Salesperson Problem,” in <i>Proceedings of the Genetic and Evolutionary Computation Conference</i>, 2020, pp. 681–689, doi: <a href=\"https://doi.org/10.1145/3377930.3389844\">10.1145/3377930.3389844</a>."}},{"status":"public","_id":"48895","publisher":"Association for Computing Machinery","page":"551–559","user_id":"102979","citation":{"bibtex":"@inproceedings{Roostapour_Bossek_Neumann_2020, place={New York, NY, USA}, series={{GECCO} ’20}, title={Runtime Analysis of Evolutionary Algorithms with Biased Mutation for the Multi-Objective Minimum Spanning Tree Problem}, DOI={<a href=\"https://doi.org/10.1145/3377930.3390168\">10.1145/3377930.3390168</a>}, booktitle={Proceedings of the 2020 Genetic and Evolutionary Computation Conference}, publisher={Association for Computing Machinery}, author={Roostapour, Vahid and Bossek, Jakob and Neumann, Frank}, year={2020}, pages={551–559}, collection={{GECCO} ’20} }","ama":"Roostapour V, Bossek J, Neumann F. Runtime Analysis of Evolutionary Algorithms with Biased Mutation for the Multi-Objective Minimum Spanning Tree Problem. In: <i>Proceedings of the 2020 Genetic and Evolutionary Computation Conference</i>. {GECCO} ’20. Association for Computing Machinery; 2020:551–559. doi:<a href=\"https://doi.org/10.1145/3377930.3390168\">10.1145/3377930.3390168</a>","mla":"Roostapour, Vahid, et al. “Runtime Analysis of Evolutionary Algorithms with Biased Mutation for the Multi-Objective Minimum Spanning Tree Problem.” <i>Proceedings of the 2020 Genetic and Evolutionary Computation Conference</i>, Association for Computing Machinery, 2020, pp. 551–559, doi:<a href=\"https://doi.org/10.1145/3377930.3390168\">10.1145/3377930.3390168</a>.","short":"V. Roostapour, J. Bossek, F. Neumann, in: Proceedings of the 2020 Genetic and Evolutionary Computation Conference, Association for Computing Machinery, New York, NY, USA, 2020, pp. 551–559.","chicago":"Roostapour, Vahid, Jakob Bossek, and Frank Neumann. “Runtime Analysis of Evolutionary Algorithms with Biased Mutation for the Multi-Objective Minimum Spanning Tree Problem.” In <i>Proceedings of the 2020 Genetic and Evolutionary Computation Conference</i>, 551–559. {GECCO} ’20. New York, NY, USA: Association for Computing Machinery, 2020. <a href=\"https://doi.org/10.1145/3377930.3390168\">https://doi.org/10.1145/3377930.3390168</a>.","ieee":"V. Roostapour, J. Bossek, and F. Neumann, “Runtime Analysis of Evolutionary Algorithms with Biased Mutation for the Multi-Objective Minimum Spanning Tree Problem,” in <i>Proceedings of the 2020 Genetic and Evolutionary Computation Conference</i>, 2020, pp. 551–559, doi: <a href=\"https://doi.org/10.1145/3377930.3390168\">10.1145/3377930.3390168</a>.","apa":"Roostapour, V., Bossek, J., &#38; Neumann, F. (2020). Runtime Analysis of Evolutionary Algorithms with Biased Mutation for the Multi-Objective Minimum Spanning Tree Problem. <i>Proceedings of the 2020 Genetic and Evolutionary Computation Conference</i>, 551–559. <a href=\"https://doi.org/10.1145/3377930.3390168\">https://doi.org/10.1145/3377930.3390168</a>"},"place":"New York, NY, USA","publication_identifier":{"isbn":["978-1-4503-7128-5"]},"author":[{"first_name":"Vahid","last_name":"Roostapour","full_name":"Roostapour, Vahid"},{"orcid":"0000-0002-4121-4668","last_name":"Bossek","first_name":"Jakob","full_name":"Bossek, Jakob","id":"102979"},{"full_name":"Neumann, Frank","last_name":"Neumann","first_name":"Frank"}],"title":"Runtime Analysis of Evolutionary Algorithms with Biased Mutation for the Multi-Objective Minimum Spanning Tree Problem","year":"2020","date_updated":"2023-12-13T10:49:38Z","language":[{"iso":"eng"}],"series_title":"{GECCO} ’20","doi":"10.1145/3377930.3390168","publication":"Proceedings of the 2020 Genetic and Evolutionary Computation Conference","extern":"1","abstract":[{"text":"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.","lang":"eng"}],"date_created":"2023-11-14T15:59:00Z","department":[{"_id":"819"}],"type":"conference","keyword":["biased mutation","evolutionary algorithms","minimum spanning tree problem","runtime analysis"]},{"citation":{"ieee":"M. Seiler, J. Pohl, J. Bossek, P. Kerschke, and H. Trautmann, “Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem,” in <i>Parallel Problem Solving from {Nature} (PPSN XVI)</i>, 2020, pp. 48–64, doi: <a href=\"https://doi.org/10.1007/978-3-030-58112-1_4\">10.1007/978-3-030-58112-1_4</a>.","apa":"Seiler, M., Pohl, J., Bossek, J., Kerschke, P., &#38; Trautmann, H. (2020). Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem. <i>Parallel Problem Solving from {Nature} (PPSN XVI)</i>, 48–64. <a href=\"https://doi.org/10.1007/978-3-030-58112-1_4\">https://doi.org/10.1007/978-3-030-58112-1_4</a>","mla":"Seiler, Moritz, et al. “Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem.” <i>Parallel Problem Solving from {Nature} (PPSN XVI)</i>, Springer-Verlag, 2020, pp. 48–64, doi:<a href=\"https://doi.org/10.1007/978-3-030-58112-1_4\">10.1007/978-3-030-58112-1_4</a>.","bibtex":"@inproceedings{Seiler_Pohl_Bossek_Kerschke_Trautmann_2020, place={Berlin, Heidelberg}, title={Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem}, DOI={<a href=\"https://doi.org/10.1007/978-3-030-58112-1_4\">10.1007/978-3-030-58112-1_4</a>}, booktitle={Parallel Problem Solving from {Nature} (PPSN XVI)}, publisher={Springer-Verlag}, author={Seiler, Moritz and Pohl, Janina and Bossek, Jakob and Kerschke, Pascal and Trautmann, Heike}, year={2020}, pages={48–64} }","short":"M. Seiler, J. Pohl, J. Bossek, P. Kerschke, H. Trautmann, in: Parallel Problem Solving from {Nature} (PPSN XVI), Springer-Verlag, Berlin, Heidelberg, 2020, pp. 48–64.","ama":"Seiler M, Pohl J, Bossek J, Kerschke P, Trautmann H. Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem. In: <i>Parallel Problem Solving from {Nature} (PPSN XVI)</i>. Springer-Verlag; 2020:48–64. doi:<a href=\"https://doi.org/10.1007/978-3-030-58112-1_4\">10.1007/978-3-030-58112-1_4</a>","chicago":"Seiler, Moritz, Janina Pohl, Jakob Bossek, Pascal Kerschke, and Heike Trautmann. “Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem.” In <i>Parallel Problem Solving from {Nature} (PPSN XVI)</i>, 48–64. Berlin, Heidelberg: Springer-Verlag, 2020. <a href=\"https://doi.org/10.1007/978-3-030-58112-1_4\">https://doi.org/10.1007/978-3-030-58112-1_4</a>."},"place":"Berlin, Heidelberg","status":"public","user_id":"102979","page":"48–64","_id":"48897","publisher":"Springer-Verlag","extern":"1","abstract":[{"lang":"eng","text":"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."}],"publication":"Parallel Problem Solving from {Nature} (PPSN XVI)","type":"conference","keyword":["Automated algorithm selection","Deep learning","Feature-based approaches","Traveling Salesperson Problem"],"department":[{"_id":"819"}],"date_created":"2023-11-14T15:59:00Z","date_updated":"2023-12-13T10:49:45Z","title":"Deep Learning as a Competitive Feature-Free Approach for Automated Algorithm Selection on the Traveling Salesperson Problem","year":"2020","publication_identifier":{"isbn":["978-3-030-58111-4"]},"author":[{"first_name":"Moritz","last_name":"Seiler","full_name":"Seiler, Moritz"},{"full_name":"Pohl, Janina","last_name":"Pohl","first_name":"Janina"},{"id":"102979","first_name":"Jakob","last_name":"Bossek","orcid":"0000-0002-4121-4668","full_name":"Bossek, Jakob"},{"last_name":"Kerschke","first_name":"Pascal","full_name":"Kerschke, Pascal"},{"full_name":"Trautmann, Heike","first_name":"Heike","last_name":"Trautmann"}],"doi":"10.1007/978-3-030-58112-1_4","language":[{"iso":"eng"}]},{"status":"public","title":"A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms","year":"2020","publication_identifier":{"issn":["1568-4946"]},"author":[{"full_name":"Bossek, Jakob","orcid":"0000-0002-4121-4668","last_name":"Bossek","first_name":"Jakob","id":"102979"},{"full_name":"Kerschke, Pascal","first_name":"Pascal","last_name":"Kerschke"},{"full_name":"Trautmann, Heike","last_name":"Trautmann","first_name":"Heike"}],"date_updated":"2023-12-13T10:52:17Z","intvolume":"        88","_id":"48848","language":[{"iso":"eng"}],"doi":"10.1016/j.asoc.2019.105901","user_id":"102979","volume":88,"publication":"Applied Soft Computing","issue":"C","citation":{"chicago":"Bossek, Jakob, Pascal Kerschke, and Heike Trautmann. “A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms.” <i>Applied Soft Computing</i> 88, no. C (2020). <a href=\"https://doi.org/10.1016/j.asoc.2019.105901\">https://doi.org/10.1016/j.asoc.2019.105901</a>.","short":"J. Bossek, P. Kerschke, H. Trautmann, Applied Soft Computing 88 (2020).","ama":"Bossek J, Kerschke P, Trautmann H. A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms. <i>Applied Soft Computing</i>. 2020;88(C). doi:<a href=\"https://doi.org/10.1016/j.asoc.2019.105901\">10.1016/j.asoc.2019.105901</a>","bibtex":"@article{Bossek_Kerschke_Trautmann_2020, title={A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms}, volume={88}, DOI={<a href=\"https://doi.org/10.1016/j.asoc.2019.105901\">10.1016/j.asoc.2019.105901</a>}, number={C}, journal={Applied Soft Computing}, author={Bossek, Jakob and Kerschke, Pascal and Trautmann, Heike}, year={2020} }","apa":"Bossek, J., Kerschke, P., &#38; Trautmann, H. (2020). A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms. <i>Applied Soft Computing</i>, <i>88</i>(C). <a href=\"https://doi.org/10.1016/j.asoc.2019.105901\">https://doi.org/10.1016/j.asoc.2019.105901</a>","mla":"Bossek, Jakob, et al. “A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms.” <i>Applied Soft Computing</i>, vol. 88, no. C, 2020, doi:<a href=\"https://doi.org/10.1016/j.asoc.2019.105901\">10.1016/j.asoc.2019.105901</a>.","ieee":"J. Bossek, P. Kerschke, and H. Trautmann, “A Multi-Objective Perspective on Performance Assessment and Automated Selection of Single-Objective Optimization Algorithms,” <i>Applied Soft Computing</i>, vol. 88, no. C, 2020, doi: <a href=\"https://doi.org/10.1016/j.asoc.2019.105901\">10.1016/j.asoc.2019.105901</a>."},"abstract":[{"lang":"eng","text":"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."}],"date_created":"2023-11-14T15:58:53Z","keyword":["Algorithm selection","Combinatorial optimization","Multi-objective optimization","Performance measurement","Traveling Salesperson Problem"],"type":"journal_article","department":[{"_id":"819"}]},{"user_id":"102979","language":[{"iso":"eng"}],"_id":"48836","date_updated":"2023-12-13T10:52:24Z","author":[{"last_name":"Bartz-Beielstein","first_name":"Thomas","full_name":"Bartz-Beielstein, Thomas"},{"last_name":"Doerr","first_name":"Carola","full_name":"Doerr, Carola"},{"full_name":"van den Berg, Daan","first_name":"Daan","last_name":"van den Berg"},{"id":"102979","full_name":"Bossek, Jakob","last_name":"Bossek","first_name":"Jakob","orcid":"0000-0002-4121-4668"},{"first_name":"Sowmya","last_name":"Chandrasekaran","full_name":"Chandrasekaran, Sowmya"},{"first_name":"Tome","last_name":"Eftimov","full_name":"Eftimov, Tome"},{"full_name":"Fischbach, Andreas","last_name":"Fischbach","first_name":"Andreas"},{"full_name":"Kerschke, Pascal","first_name":"Pascal","last_name":"Kerschke"},{"full_name":"Cava, William La","first_name":"William La","last_name":"Cava"},{"last_name":"Lopez-Ibanez","first_name":"Manuel","full_name":"Lopez-Ibanez, Manuel"},{"full_name":"Malan, Katherine M.","first_name":"Katherine M.","last_name":"Malan"},{"full_name":"Moore, Jason H.","last_name":"Moore","first_name":"Jason H."},{"first_name":"Boris","last_name":"Naujoks","full_name":"Naujoks, Boris"},{"last_name":"Orzechowski","first_name":"Patryk","full_name":"Orzechowski, Patryk"},{"full_name":"Volz, Vanessa","last_name":"Volz","first_name":"Vanessa"},{"full_name":"Wagner, Markus","last_name":"Wagner","first_name":"Markus"},{"last_name":"Weise","first_name":"Thomas","full_name":"Weise, Thomas"}],"title":"Benchmarking in Optimization: Best Practice and Open Issues","year":"2020","status":"public","department":[{"_id":"819"}],"type":"journal_article","date_created":"2023-11-14T15:58:51Z","citation":{"chicago":"Bartz-Beielstein, Thomas, Carola Doerr, Daan van den Berg, Jakob Bossek, Sowmya Chandrasekaran, Tome Eftimov, Andreas Fischbach, et al. “Benchmarking in Optimization: Best Practice and Open Issues.” <i>Corr</i>, 2020.","short":"T. Bartz-Beielstein, C. Doerr, D. van den Berg, J. Bossek, S. Chandrasekaran, T. Eftimov, A. Fischbach, P. Kerschke, W.L. Cava, M. Lopez-Ibanez, K.M. Malan, J.H. Moore, B. Naujoks, P. Orzechowski, V. Volz, M. Wagner, T. Weise, Corr (2020).","ieee":"T. Bartz-Beielstein <i>et al.</i>, “Benchmarking in Optimization: Best Practice and Open Issues,” <i>Corr</i>, 2020.","apa":"Bartz-Beielstein, T., Doerr, C., van den Berg, D., Bossek, J., Chandrasekaran, S., Eftimov, T., Fischbach, A., Kerschke, P., Cava, W. L., Lopez-Ibanez, M., Malan, K. M., Moore, J. H., Naujoks, B., Orzechowski, P., Volz, V., Wagner, M., &#38; Weise, T. (2020). Benchmarking in Optimization: Best Practice and Open Issues. <i>Corr</i>.","bibtex":"@article{Bartz-Beielstein_Doerr_van den Berg_Bossek_Chandrasekaran_Eftimov_Fischbach_Kerschke_Cava_Lopez-Ibanez_et al._2020, title={Benchmarking in Optimization: Best Practice and Open Issues}, journal={Corr}, 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 et al.}, year={2020} }","ama":"Bartz-Beielstein T, Doerr C, van den Berg D, et al. Benchmarking in Optimization: Best Practice and Open Issues. <i>Corr</i>. Published online 2020.","mla":"Bartz-Beielstein, Thomas, et al. “Benchmarking in Optimization: Best Practice and Open Issues.” <i>Corr</i>, 2020."},"publication":"Corr"},{"citation":{"bibtex":"@book{Fastlabend-Vargas_2020, place={Zwischentöne.info }, title={Geschichte(n) der deutschen Migrationsgesellschaft. Jugendliche erzählen begründete historische Geschichten Eine Unterrichtsreihe für das Portal Zwischentöne.info }, publisher={Zwischentöne.info }, author={Fastlabend-Vargas, Daniel}, year={2020} }","short":"D. Fastlabend-Vargas, Geschichte(n) der deutschen Migrationsgesellschaft. Jugendliche erzählen begründete historische Geschichten Eine Unterrichtsreihe für das Portal Zwischentöne.info , Zwischentöne.info , Zwischentöne.info , 2020.","ama":"Fastlabend-Vargas D. <i>Geschichte(n) der deutschen Migrationsgesellschaft. Jugendliche erzählen begründete historische Geschichten Eine Unterrichtsreihe für das Portal Zwischentöne.info </i>. Zwischentöne.info ; 2020.","chicago":"Fastlabend-Vargas, Daniel. <i>Geschichte(n) der deutschen Migrationsgesellschaft. Jugendliche erzählen begründete historische Geschichten Eine Unterrichtsreihe für das Portal Zwischentöne.info </i>. Zwischentöne.info : Zwischentöne.info , 2020.","ieee":"D. Fastlabend-Vargas, <i>Geschichte(n) der deutschen Migrationsgesellschaft. Jugendliche erzählen begründete historische Geschichten Eine Unterrichtsreihe für das Portal Zwischentöne.info </i>. Zwischentöne.info : Zwischentöne.info , 2020.","apa":"Fastlabend-Vargas, D. (2020). <i>Geschichte(n) der deutschen Migrationsgesellschaft. Jugendliche erzählen begründete historische Geschichten Eine Unterrichtsreihe für das Portal Zwischentöne.info </i>. Zwischentöne.info .","mla":"Fastlabend-Vargas, Daniel. <i>Geschichte(n) der deutschen Migrationsgesellschaft. Jugendliche erzählen begründete historische Geschichten Eine Unterrichtsreihe für das Portal Zwischentöne.info </i>. 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Welser anlässlich der Verleihung der Ehrendoktorwürde am 14.11.2019 durch die kulturwissenschaftliche Fakultät der Universität Paderborn}, number={155}, journal={PUR [= Paderborner Universitätsreden. Hg. von. Prof. em. Dr. Dr. hc. malt. Peter Freese]}, author={Autsch, Sabiene}, year={2020}, pages={18–22} }","mla":"Autsch, Sabiene. “Festrede auf Maria v. Welser anlässlich der Verleihung der Ehrendoktorwürde am 14.11.2019 durch die kulturwissenschaftliche Fakultät der Universität Paderborn.” <i>PUR [= Paderborner Universitätsreden. Hg. von. Prof. em. Dr. Dr. hc. malt. Peter Freese]</i>, no. 155, 2020, pp. 18–22."},"date_created":"2023-12-20T14:42:38Z","type":"newspaper_article"},{"_id":"50105","language":[{"iso":"ger"}],"page":"S. 12-17","user_id":"78235","author":[{"id":"78235","full_name":"Pauls, Karina","first_name":"Karina","last_name":"Pauls"}],"title":"Alice im Wunderland. 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