MRM: Site Selection via Mutil-round Meanshift for Global Fairness

Elevator maintenance plays an important role in the safety and economic aspects of daily life, and the location of elevator maintenance sites is crucial in this scenario. A reasonable location can help reduce economic expenses and ensure the healthy operation of the system of maintenance sites. However, due to the lack of candidate location sets and unevenly distributed data layers, existing coverage siting methods have difficulties and challenges in solving this problem, and ignore the fairness of load among different sites. To address above problems, We propose a heuristic coverage siting method called MRM, which is based on multi-round MeanShift clustering with coverage radius variation. Experiments on a real elevator dataset with noise show that MRM not only achieves 99.21 % coverage with fewer sites but also achieves fairly good global fairness.