@misc{LoefflerBeckerHofstedt, author = {L{\"o}ffler, Sven and Becker, Ilja and Hofstedt, Petra}, title = {Enhancing constraint optimization problems with greedy search and clustering: a focus on the traveling salesman problem}, series = {Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART}, journal = {Proceedings of the 16th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART}, publisher = {SCITEPRESS - Science and Technology Publications}, isbn = {978-989-758-680-4}, issn = {2184-433X}, doi = {10.5220/0012453000003636}, pages = {1170 -- 1178}, language = {en} } @misc{LoefflerHofstedt, author = {L{\"o}ffler, Sven and Hofstedt, Petra}, title = {A constraint-based greedy-local-global search for the warehouse location problem}, series = {IFIP Advances in Information and Communication Technology}, journal = {IFIP Advances in Information and Communication Technology}, publisher = {Springer Nature Switzerland}, address = {Cham}, isbn = {9783031632181}, issn = {1868-4238}, doi = {10.1007/978-3-031-63219-8_22}, pages = {291 -- 304}, language = {en} } @misc{FrankBuckelHoegneretal., author = {Frank, Florian and Buckel, Peter and Hoegner, Ludwig and Hofstedt, Petra}, title = {A landmark selection method for object-based visual outdoor localization approaches of automated ground vehicles}, series = {ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences}, journal = {ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences}, publisher = {Copernicus GmbH}, issn = {2194-9050}, doi = {10.5194/isprs-annals-X-4-W5-2024-163-2024}, pages = {163 -- 169}, abstract = {Autonomous vehicles must navigate independently in an outdoor environment using features or objects. However, some objects may be more or less suitable for localization due to their attributes. Therefore, this work investigates the suitability of landmarks for camera- and object-based outdoor localization methods. First, object attributes are methodically derived from the requirements of object-based localization. The physical representation on the camera image plane, probability of occurrence, and persistence were identified as influencing the object localization suitability. The influence of the object's camera image plane representation regarding object recognition algorithms is not considered or discussed, but advice on the minimum object pixel size is provided. The first milestone was the creation of an equation for object localization suitability calculation by normalizing and multiplying the identified attributes. Simultaneously, potential objects from the outdoor environment were identified, resulting in a structured object catalog. The results of the equation and catalog are a ranked according to the object localization suitability in a comparison table. Our comparison demonstrates that objects such as buildings or trees are more suitable than street lane markings for self-localization. However, most current datasets do not include the proposed instantiated objects. The paper addresses this issue, assists in the object selection for outdoor localization methods and provides input for the creation of future-oriented datasets and autonomous driving maps.}, language = {en} } @misc{BeckerLoefflerHofstedt, author = {Becker, Ilja and L{\"o}ffler, Sven and Hofstedt, Petra}, title = {ML-based Automation of Constraint Satisfaction Model Transformation and Solver Configuration}, series = {Distributed Computing and Artificial Intelligence, Special Sessions - DCAI 2022, 19th International Conference}, journal = {Distributed Computing and Artificial Intelligence, Special Sessions - DCAI 2022, 19th International Conference}, editor = {Machado, Jose Manuel F. and Chamoso, Pablo and Hernandez, Guillermo and Bocewicz, Grzegorz and Loukanova, Roussanka and Jove, Esteban and del Rey, Angel Martin and Ricca, Michela}, publisher = {Springer}, address = {Cham}, isbn = {978-3-031-23209-1}, pages = {177 -- 183}, language = {en} } @misc{LoefflerBeckerHofstedt, author = {L{\"o}ffler, Sven and Becker, Ilja and Hofstedt, Petra}, title = {A Finite-Domain Constraint-Based Approach on the Stockyard Planning Problem}, series = {Database and Expert Systems Applications : 34th International Conference, DEXA 2023, Penang, Malaysia, August 28-30, 2023, Proceedings, Part II}, journal = {Database and Expert Systems Applications : 34th International Conference, DEXA 2023, Penang, Malaysia, August 28-30, 2023, Proceedings, Part II}, editor = {Strauss, Christine and Amagasa, Toshiyuki and Kotsis, Gabriele and Tjoa, A Min and Khalil, Ismail}, publisher = {Springer}, address = {Cham}, isbn = {978-3-031-39820-9}, pages = {126 -- 133}, language = {en} } @misc{BelsLoefflerBeckeretal., author = {Bels, Maximilian and L{\"o}ffler, Sven and Becker, Ilja and Hofstedt, Petra}, title = {Constraint-Based Filtering and Evaluation of CSP Search Trees}, series = {Proceedings of the 15th International Conference on Agents and Artificial Intelligence - ICAART 2023, Volume 3}, journal = {Proceedings of the 15th International Conference on Agents and Artificial Intelligence - ICAART 2023, Volume 3}, editor = {Rocha, Ana Paula and Steels, Luc and van den Herik, H. Jaap}, publisher = {Scitepress}, isbn = {978-989-758-623-1}, doi = {10.5220/0011641100003393}, pages = {220 -- 227}, language = {en} } @misc{LoefflerBeckerBueckertetal., author = {L{\"o}ffler, Sven and Becker, Ilja and B{\"u}ckert, Carlo and Hofstedt, Petra}, title = {Enhanced Optimal Beacon Placement for Indoor Positioning: A Set Variable Based Constraint Programming Approach}, series = {Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics : November 13-15, 2023, in Rome, Italy, volume 1}, journal = {Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics : November 13-15, 2023, in Rome, Italy, volume 1}, editor = {Gini, Giuseppina and Nijmeijer, Henk and Filev, Dimitar}, publisher = {Scitepress}, isbn = {978-989-758-670-5}, doi = {10.5220/0012203400003543}, pages = {70 -- 79}, language = {en} } @misc{LoefflerBeckerHofstedtetal., author = {L{\"o}ffler, Sven and Becker, Ilja and Hofstedt, Petra and Nitze, Andre and Hennig, Silvia and Klinge, Alexander}, title = {Planung des L{\"a}ndlichen On-Demand-Verkehr - Probleme, Analyse und Algorithmen}, series = {Informatik 2023 : Designing Futures - Zuk{\"u}nfte gestalten : 26.-29. September 2023, Berlin}, journal = {Informatik 2023 : Designing Futures - Zuk{\"u}nfte gestalten : 26.-29. September 2023, Berlin}, editor = {Klein, Maike and Krupka, Daniel and Winter, Cornelia and Wohlgemuth, Volker}, publisher = {Gesellschaft f{\"u}r Informatik e.V.}, address = {Berlin}, isbn = {978-3-88579-731-9}, doi = {10.18420/inf2023_177}, pages = {1739 -- 1750}, language = {de} } @misc{PissarekHofstedtLoeffler, author = {Pißarek, Adele and Hofstedt, Petra and L{\"o}ffler, Sven}, title = {Stockyard Planning and Optimization Using Intelligent Search}, series = {Innovative Intelligent Industrial Production and Logistics}, volume = {2}, journal = {Innovative Intelligent Industrial Production and Logistics}, editor = {Dassisti, Michele and Madani, Kurosh and Panetto, Herve}, publisher = {Springer Nature Switzerland}, address = {Cham}, isbn = {978-3-031-80775-6}, issn = {1865-0937}, doi = {10.1007/978-3-031-80775-6_7}, pages = {94 -- 110}, language = {en} } @incollection{LoefflerHofstedt, author = {L{\"o}ffler, Sven and Hofstedt, Petra}, title = {A constraint-based savings algorithm for the Traveling Salesman Problem}, series = {Machine Learning, Optimization and Data Science : 10th International Conference, LOD 2024, Castiglione Della Pescaia, Italy, September 22-25, 2024, Revised Selected Papers}, volume = {2}, booktitle = {Machine Learning, Optimization and Data Science : 10th International Conference, LOD 2024, Castiglione Della Pescaia, Italy, September 22-25, 2024, Revised Selected Papers}, editor = {Nicosia, Guiseppe and Ojha, Varun and Giesselbach, Sven and Pardalos, M. Panos and Umeton, Renato}, publisher = {Springer Nature Switzerland}, address = {Cham}, isbn = {9783031824838}, issn = {0302-9743}, doi = {10.1007/978-3-031-82484-5_15}, pages = {203 -- 217}, abstract = {There exists a plethora of NP-hard problems for which obtaining an exact solution is computationally intensive while an approximate solution can be rapidly computed. The Traveling Salesman Problem (TSP) stands out as a prominent example within this problem class, being equally significant in both research and industry sectors. Exact methods for solving the TSP are typically infeasible within acceptable timeframes beyond a certain instance size. Due to the NP-hardness of the problem, computational time requirements would quickly escalate to weeks, months, years, or even millennia. In contrast, heuristic approaches often yield sufficiently good solutions rapidly, typically within seconds or minutes. However, the drawback lies in their tendency to produce only locally optimal solutions, which may deviate significantly from a global optimum. Nevertheless, heuristic methods remain preferred in industry due to their ability to find satisfactory solutions within reasonable timeframes. It is worth noting that even marginal improvements in solutions can translate into significant cost savings in practice. Hence, there is a demand for methods capable of swiftly providing high-quality solutions while also continuously searching for further, better solutions over time. This work aims to combine two approaches: heuristic search (utilizing two simple greedy algorithms and the savings algorithm developed by Clarke and Wright) and exact search (constraint programming), to solve TSPs. Using various TSP instances, we demonstrate that our approach yields a better solution than purely local methods in at least 80\% of the cases. Furthermore, within the given time limit of 5 min, the new approach identifies a solution that is more than twice as good compared to traditional COP methods.}, language = {en} }