Heuristic methods for minimal controller location set problem in transportation networks

Abstract

To be used efficiently, transportation networks require control strategies to optimize flow distribution. However, the location and type of controllers employed in a transportation network directly impact the level of performance reachable by traffic control policies. In order to guarantee that the highest level of performance is reachable, fully exploiting the available network capacity and reducing negative externalities, we explore methods to identify relevant controller locations in transportation networks while minimizing the number of controllers used. Previous work provided an exact approach to identify controller locations on complex networks. However, said approach exhibits complications when applied to transportation networks containing bi-directional links. We therefore propose simple heuristic algorithms relying only on topological information to solve this problem, while also avoiding heavy computation, thus being able to determine a solution to the minimal controller location set problem on large networks. Based on the existing framework, we aim to provide an experimental setup, with diverse network sizes and configurations to analyze the performances of different heuristic methods, in order to develop an efficient algorithm.