City Logistics

Abstract

This paper addresses freight management in large, congested urban settings. Congestion creates a substantial variation in travel time (speeds) during morning peak and evening peak periods. Besides the day-to-day dynamics of traffic conditions, traffic incidents contribute significantly to urban congestion, resulting in unplanned travel delays. Urban route designs that ignore such significant variations are often found to be inefficient or even infeasible (in regard to delivery or pickup time windows) in a congested traffic environment. This limitation may lead to delays, higher operational costs, and inferior customer service. To take the dynamics of traffic conditions into account, the proposed modeling framework includes an underlying dynamic network traffic simulation-assignment model that is able to compute time-dependent shortest paths (TDSPs) and simulate individual vehicles on a realistic representation of urban road network elements, including signalization, ramp metering, and other operational controls. A two-phase set-partitioning–based heuristic approach is proposed to construct freight vehicle routes. No parameter tuning is required. The integrated modeling framework was first tested on a small network, and then the application was demonstrated on a real-world urban network, the Chicago, Illinois, area network, with problem instances of up to 500 customers with TDSPs updated at 10-min intervals.