A hybrid heuristic approach for traffic light synchronization based on the MAXBAND

Abstract

This study addresses a high resolution model for the synchronization of traffic lights on transport networks. A hybrid heuristic algorithm optimizes the mixed integer linear model, referred as MAXBAND, seeking to achieve maximal bandwidth by setting arterial signals. The assessed algorithm corresponds to a hybrid metaheuristic which combines Tabu Search and Variable Neighborhood Search. The algorithm uses a memory structure within an iterative local search, allowing a broader diversity of solutions. In addition, some adjustments were incorporated to the MAXBAND such as the revision of the constraints of the mixed integer linear model, including those that describe all the cyclic routes in the graph, and some bounds were generalized for integer variables. Extensive computational experiments were carried out evidencing a competitive performance for large instances.