TY - GEN A1 - Löffler, Sven A1 - Abbenhaus, Viktoria A1 - Assaf, George A1 - Hofstedt, Petra ED - Gini, Giuseppina ED - Precup, Radu-Emil ED - Filev, Dimitar P. T1 - Solving the three-dimensional beacon placement problem using constraint-based methods, large neighborhood search, and evolutionary algorithms T2 - Proceedings of the 22nd International Conference on Informatics in Control, Automation and Robotics : Volume 1 : ICINCO N2 - With the increasing prevalence of large building complexes, indoor localization is becoming an area of growing significance. In critical situations, such as emergencies in factories or care facilities, the ability to locate a person quickly can be a matter of life and death. One possibility for localization are Bluetooth beacons, which are either attached to the person or in rooms. We pursue the latter approach, whereby the beacon signals are used to determine the position of a receiving device, e.g. a mobile phone. At this, the use of a sufficient number of beacons in the building must be ensured in order to guarantee adequate coverage. However, to minimize costs, it is equally important to avoid placing unnecessary beacons. This creates a challenging optimization problem that this paper addresses through three distinct approaches: constraint programming, large neighborhood search, and evolutionary algorithms. Using simulated three-dimensional buildings, we test and evaluate these m ethods, ultimately providing a practical and efficient approach applicable to real-world building environments. KW - Constraint Programming KW - AI Algorithms KW - Beacon Placement Y1 - 2025 SN - 978-989-758-770-2 U6 - https://doi.org/10.5220/0013724500003982 SP - 105 EP - 116 PB - SciTePress - Science and Technology Publications CY - Setúbal, Portugal ER - TY - CHAP A1 - Löffler, Sven A1 - Abbenhaus, Viktoria A1 - Assaf, George A1 - Hofstedt, Petra ED - Braun, Tanya ED - Paaßen, Benjamin ED - Stolzenburg, Frieder T1 - A hybrid constraint-based, greedy, and local search approach for the transshipment problem T2 - KI 2025 : advances in artificial intelligence : 48th German Conference on AI, Potsdam, Germany, September 16–19, 2025 : proceedings N2 - The efficient resolution of logistics problems, particularly those aimed at minimizing costs and reducing environmental impact, represents a critical challenge in our globalized world. A prominent example of such problems is the Transshipment Problem, which seeks to determine the most cost-effective paths from sources (e.g., producers) through transshipment points to sinks (e.g., customers). Approaches to addressing this problem range from greedy algorithms, which may rapidly yield locally optimal solutions, to constraint-based methods that, given sufficient resources and computation time, can identify globally optimal solutions. In this study, we propose a hybrid approach that integrates greedy strategies into the solution process of constraint modeling for the Transshipment Problem. This integration aims to expedite the discovery of high-quality initial solutions while preserving the global optimization capabilities inherent in constraint-based search methods. To validate the effectiveness of this new hybrid approach, we conducted an extensive series of experiments, which demonstrate its significant advantages in solving the Transshipment Problem compared to both a conventional constraint model and pure greedy methods. KW - Constraint Programming KW - Search methods KW - Transshipment problem Y1 - 2025 SN - 978-3-032-02813-6 U6 - https://doi.org/10.1007/978-3-032-02813-6_7 SN - 0302-9743 SP - 91 EP - 103 PB - Springer Nature Switzerland CY - Cham ER -