In late 2015 three of the co-authors of this paper published the first review on time-dependent routing problems. Since then, there have been several important algorithmic developments in the field. These include travel time prediction methods, real-time re-optimization by operating directly on the road graph, efficient exploration of solution neighborhoods, dynamic discretization discovery and Machine Learning-inspired methods. The aim of this survey is to present such research lines, together with indications on their further developments.
Dynamic demand-responsive transit scheduling with time-dependent travel times: A joint supply and demand management approach
Demand-responsive transit (DRT) is a flexible public transportation mode offering affordable door-to-door services. However, its widespread adoption still faces large hurdles such as demand variability, immediacy, and financial sustainability. Most DRT studies focus on fleet management, often leading to underutilization …