Indoor localization plays a key role across diverse environments such as hospitals, retirement homes, and emergency response scenarios. Ensuring the efficient and precise tracking of mobile individuals indoors heavily relies on the strategic deployment of sensors. Manual placement of beacons (sensors) for indoor positioning within a building poses significant challenges and time constraints. Consequently, numerous researchers have explored this problem domain, employing diverse algorithms and addressing various practical scenarios. In our previous works at the ACS/IEEE International Conference on Computer Systems and Applications (AICCSA 2022) [20] and the 20th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2023) [19], we introduced two novel approaches that leverage constraint programming with exclusively Boolean variables respectively only set variables and Boolean variables to efficiently place Bluetooth Low Energy (BLE) beacons in indoor scenarios. We evaluated the quality of our results by comparing them against manually optimized beacon placement and assessing their performance in four real-world school buildings. This paper extends the findings of [19, 20] by new approaches on the search in the constraint solving process using greedy search and local search techniques.