A Heuristic Algorithm for Traffic Light Synchronization Based on the MAXBAND Model

TL;DR

This paper presents a heuristic algorithm combining Tabu Search and Variable Neighbourhood Search to efficiently solve large-scale traffic light synchronization problems modeled by MAXBAND, surpassing the limitations of exact solvers.

Contribution

It introduces a generalized formulation of the MAXBAND model including cycle constraints and proposes a novel heuristic algorithm for large instances.

Findings

The heuristic outperforms exact methods on large instances.

The generalized model accurately captures cycle constraints.

The algorithm achieves high-quality solutions efficiently.

Abstract

A widely used approach to solve the synchronization of traffic lights on transport networks is the maximization of the time during which cars start at one end of a street and can go to the other without stopping for a red light (bandwidth maximization). The mixed integer linear model found in the literature, named MAXBAND, can be solved by optimization solvers only for small instances. In this paper we review in detail all the constraints of the original linear model, including those that describe all the cyclic routes in the graph, and we generalize some bounds for integer variables which so far had been presented only for problems that do not consider cycles. Finally, we propose a solution algorithm that uses Tabu Search and Variable Neighbourhood Search and we carry out a computational study to show that it performs very well for large instances.