Research on dynamic and stochastic vehicle routing problems received increasing interest in the last decade. It considers a novel problem class, aiming at an appropriate handling of dynamic events combined with the incorporation of stochastic information about possible future events. This survey summarises the recent literature in this area. Besides, the classification according to the available stochastic information, a new classification based on the point in time where substantial computational effort for determining decisions or decision policies arises, is introduced. Furthermore, the difference in solution quality is analysed between approaches which consider either purely dynamic or stochastic problems compared to those which consider both, stochastic and dynamic aspects. A graphical representation demonstrates the strength of the reviewed approaches incorporating dynamic and stochastic information. The survey also gives an overview on the intensity of research for the different problem classes and its benefit in recent years. Finally, guidelines and promising directions for further research are presented.

The organization of a specialized transportation system to perform transports for elderly and handicapped people is usually modeled as dial-a-ride problem. Users place transportation requests with specified pickup and delivery locations and times. The requests have to be completed under user inconvenience considerations by a specified fleet of vehicles. In the dial-a-ride problem, the aim is to minimize the total travel times respecting the given time windows, the maximum user ride times, and the vehicle restrictions. This paper introduces a dynamic programming algorithm for the dial-a-ride problem and demonstrates its effective application in (hybrid) metaheuristic approaches. Compared to most of the works presented in literature, this approach does not make use of any (commercial) solver. We present an exact dynamic programming algorithm and a dynamic programming based metaheuristic, which restricts the considered solution space. Then, we propose a hybrid metaheuristic algorithm which integrates the dynamic programming based algorithms into a large neighborhood framework. The algorithms are tested on a given set of benchmark instances from the literature and compared to a state-of-the-art hybrid large neighborhood search approach.

Population growth in cities and expanding city territory as well as population decline in rural areas pose a challenge for the existing transport network. Consequently, we observe a rapid change in transport infrastructure and transportation technology within the last few years. Due to novelty or differentness, it will initially be challenging to integrate them into the existing network in Western European cities and to identify suitable corridors leading to especially beneficial effects on the overall transport network. The effects of new technologies and (high-performance) infrastructures are hardly examined. It remains unclear how these novel transportation technologies will change society, our understanding of spatial proximity, mobility, and consequently the logistics sector. In this work, we give an overview regarding first considerations and reflections on the impacts of the changes and developments in the field of freight transportation. Our work mainly focusses on the estimation of the impacts of high-performance transport technologies on the society, spatial proximity, and the logistics sector while extending the European transportation network accordingly. In our understanding, we refer to high-performance transportation technologies as mobility systems with either high throughput (fast and/or high utilization loads) or very flexible application. To be more specific, we focus on Hyperloop technologies, Cargo-Sous-Terrain, freight airships, and drones.