Real-time fleet optimization in urban freight distribution using real traffic data

Abstract:

Freight distribution is one of the main components of city logistics. The use of intelligent transportation systems and
technological advances in communication and information has made it possible to integrate freight transportation management
with network traffic elements. This paper provides a framework for real-time management of the freight distribution fleet under
real-time traffic conditions. In this framework, the freight distribution process was optimized under traffic conditions and
network events. The main innovation of this article was the simultaneous optimization of the routes (sequence of customers) and
the paths (sequence of roads between customers). The presented framework uses two modules: shortest path module and routing
and scheduling module, to optimize fleet performance and costs based on real-time data. In the computational experiment in the
current research, the real network was used. Real-time traffic data was received from Google Maps at specified intervals, and
the simulator program (Python) simulated freight distribution operations. Experimental results showed using this framework,
fleet travel time would reduce 9% in wide time windows and 11% in the narrow time windows. Although early time service had
not changed significantly in the narrow time windows scenario, but late service time reduced about 14%.

Keywords: Freight distribution, Real-time traffic data, Real-time fleet management