@inproceedings{SchiendorferSteghoeferKnappetal.2013, author = {Schiendorfer, Alexander and Stegh{\"o}fer, Jan-Philipp and Knapp, Alexander and Nafz, Florian and Reif, Wolfgang}, title = {Constraint Relationships for Soft Constraints}, booktitle = {Research and Development in Intelligent Systems XXX: Incorporating Applications and Innovations in Intelligent Systems XXI: Proceedings of AI-2013}, editor = {Bramer, Max and Petridis, Miltos}, publisher = {Springer}, address = {Cham}, isbn = {978-3-319-02621-3}, doi = {https://doi.org/10.1007/978-3-319-02621-3_17}, pages = {241 -- 255}, year = {2013}, language = {en} } @inproceedings{KnappSchiendorferReif2014, author = {Knapp, Alexander and Schiendorfer, Alexander and Reif, Wolfgang}, title = {Quality over Quantity in Soft Constraints}, booktitle = {Proceedings: 2014 IEEE 26th International Conference on Tools with Artificial Intelligence: ICTAI 2014}, publisher = {IEEE}, address = {Los Alamitos}, isbn = {978-1-4799-6572-4}, doi = {https://doi.org/10.1109/ICTAI.2014.75}, pages = {453 -- 460}, year = {2014}, language = {en} } @inbook{SchiendorferKnappSteghoeferetal.2015, author = {Schiendorfer, Alexander and Knapp, Alexander and Stegh{\"o}fer, Jan-Philipp and Anders, Gerrit and Siefert, Florian and Reif, Wolfgang}, title = {Partial Valuation Structures for Qualitative Soft Constraints}, booktitle = {Software, Services, and Systems: Essays Dedicated to MartinWirsing on the Occasion of His Retirement from the Chair of Programming and Software Engineering}, editor = {De Nicola, Rocco and Hennicker, Rolf}, publisher = {Springer}, address = {Cham}, isbn = {978-3-319-15545-6}, doi = {https://doi.org/10.1007/978-3-319-15545-6_10}, pages = {115 -- 133}, year = {2015}, language = {en} } @article{SchiendorferKnappAndersetal.2018, author = {Schiendorfer, Alexander and Knapp, Alexander and Anders, Gerrit and Reif, Wolfgang}, title = {MiniBrass: Soft constraints for MiniZinc}, volume = {23}, journal = {Constraints}, number = {4}, publisher = {Springer}, address = {Dodrecht}, issn = {1572-9354}, doi = {https://doi.org/10.1007/s10601-018-9289-2}, pages = {403 -- 450}, year = {2018}, language = {en} } @inproceedings{StieberHoffmannSchiendorferetal.2020, author = {Stieber, Simon and Hoffmann, Alwin and Schiendorfer, Alexander and Reif, Wolfgang and Beyrle, Matthias and Faber, Jan and Richter, Michaela and Sause, Markus}, title = {Towards real-time process monitoring and machine learning for manufacturing composite structures}, booktitle = {Proceedings 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-7281-8956-7}, issn = {1946-0759}, doi = {https://doi.org/10.1109/ETFA46521.2020.9212097}, pages = {1455 -- 1458}, year = {2020}, language = {en} } @inproceedings{GajekSchiendorferReif2019, author = {Gajek, Carola and Schiendorfer, Alexander and Reif, Wolfgang}, title = {A chained neural network model for photovoltaic power forecast}, booktitle = {Machine Learning, Optimization, and Data Science: 5th International Conference, LOD 2019, Siena, Italy, September 10-13, 2019, Proceedings}, editor = {Nicosia, Giuseppe and Pardalos, Panos and Umeton, Renato and Giuffrida, Giovanni and Sciacca, Vincenzo}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-37598-0}, issn = {0302-9743}, doi = {https://doi.org/10.1007/978-3-030-37599-7_47}, pages = {566 -- 578}, year = {2019}, language = {en} } @inproceedings{GajekSchiendorferReif2023, author = {Gajek, Carola and Schiendorfer, Alexander and Reif, Wolfgang}, title = {A Recommendation System for CAD Assembly Modeling based on Graph Neural Networks}, booktitle = {Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2022, Proceedings, Part I}, editor = {Amini, Massih-Reza and Canu, St{\´e}phane and Fischer, Asja and Guns, Tias and Kralj Novak, Petra and Tsoumakas, Grigorios}, publisher = {Springer}, address = {Cham}, isbn = {978-3-031-26387-3}, doi = {https://doi.org/10.1007/978-3-031-26387-3_28}, pages = {457 -- 473}, year = {2023}, language = {en} } @inproceedings{SchiendorferSteghoeferReif2014, author = {Schiendorfer, Alexander and Stegh{\"o}fer, Jan-Philipp and Reif, Wolfgang}, title = {Synthesis and Abstraction of Constraint Models for Hierarchical Resource Allocation Problems}, booktitle = {Proceedings of the 6th International Conference on Agents and Artificial Intelligence: Volume 2: ICAART}, publisher = {SciTePress}, address = {Set{\´u}bal}, isbn = {978-989-758-016-1}, doi = {https://doi.org/10.5220/0004757700150027}, pages = {15 -- 27}, year = {2014}, abstract = {Many resource allocation problems are hard to solve even with state-of-the-art constraint optimisation software upon reaching a certain scale. Our approach to deal with this increasing complexity is to employ a hierarchical "regio-central" mechanism. It requires two techniques: (1) the synthesis of several models of agents providing a certain resource into a centrally and efficiently solvable optimisation problem and (2) the creation of an abstracted version of this centralised model that reduces its complexity when passing it on to higher layers. We present algorithms to create such synthesised and abstracted models in a fully automated way and demonstrate empirically that the obtained solutions are comparable to central solutions but scale better in an example taken from energy management.}, language = {en} } @inproceedings{SchiendorferLassnerAndersetal.2015, author = {Schiendorfer, Alexander and Lassner, Christoph and Anders, Gerrit and Reif, Wolfgang and Lienhart, Rainer}, title = {Active Learning for Efficient Sampling of Control Models of Collectives}, booktitle = {Proceedings: 2015 IEEE 9th International Conference on Self-Adaptive and Self-Organizing Systems: SASO 2015}, publisher = {IEEE}, address = {Los Alamitos}, doi = {https://doi.org/10.1109/SASO.2015.13}, pages = {51 -- 60}, year = {2015}, language = {en} } @article{StieberSchroeterFausteretal.2022, author = {Stieber, Simon and Schr{\"o}ter, Niklas and Fauster, Ewald and Bender, Marcel and Schiendorfer, Alexander and Reif, Wolfgang}, title = {Inferring material properties from FRP processes via sim-to-real learning}, volume = {128}, journal = {The International Journal of Advanced Manufacturing Technology}, number = {3-4}, publisher = {Springer}, address = {London}, issn = {1433-3015}, doi = {https://doi.org/10.1007/s00170-023-11509-8}, pages = {1517 -- 1533}, year = {2022}, abstract = {Fiber reinforced polymers (FRP) provide favorable properties such as weight-specific strength and stiffness that are central for certain industries, such as aerospace or automotive manufacturing. Liquid composite molding (LCM) is a family of often employed, inexpensive, out-of-autoclave manufacturing techniques. Among them, resin transfer molding (RTM), offers a high degree of automation. Herein, textile preforms are saturated by a fluid polymer matrix in a closed mold.Both impregnation quality and level of fiber volume content are of crucial importance for the final part quality. We propose to simultaneously learn three major textile properties (fiber volume content and permeability in X and Y direction) presented as a three-dimensional map based on a sequence of camera images acquired in flow experiments and compare CNNs, ConvLSTMs, and Transformers. Moreover, we show how simulation-to-real transfer learning can improve a digital twin in FRP manufacturing, compared to simulation-only models and models based on sparse real data. The overall best metrics are: IOU 0.5031 and Accuracy 95.929 \%, obtained by pretrained transformer models.}, language = {en} }