Advanced algorithms for optimal meeting points in road networks

Abstract

An optimal meeting point query is used to determine a location in a spatial region to build a new facility that minimizes the sum of the (weighted) road distances from all clients. This problem has been studied in previous work with the assumption that all clients and facilities reside in Euclidean space or along road networks. However, due to the limitations of geographic information system technologies, it is difficult to return an exact geographic location to answer the optimal meeting point query based on a set of arbitrary coordinates. This issue results in various problems, such as positioning and measurement errors, in practical use. In this paper, it is aimed to identify the optimal meeting point in road networks for clients and facilities residing in non-Euclidean spaces. Two efficient heuristic solutions are proposed based on approximate and adaptive query processing techniques by using randomized adaptive search and random direction search methods, respectively, to rapidly converge to the global optimum in the geographic coordinate system. Extensive experiments based on real datasets demonstrate that our proposed method achieves a 32.11% improvement over the state-of-the-art approach.