On the truck dispatching problem

Chapter headings: Introduction. Modelling city logistics. City logistics with ITS. Demand and supply models. Impact models. Vehicle routing and scheduling. Vehicle routing and scheduling with ITS. Location of logistics terminals. Future perspectives. References. Index.

City logistics : network modelling and intelligent transport systems

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS Editor-In-Chief

Online vehicle routing is an important task of the modern transportation service provider. Contributed by the ever-increasing real-time demand on the transportation system, especially small-parcel last-mile delivery requests, vehicle route generation is becoming more computationally complex than before. The existing routing algorithms are mostly based on mathematical programming, which requires huge computation time in city-size transportation networks. To develop routes with minimal time, in this paper, we propose a novel deep reinforcement learning-based neural combinatorial optimization strategy. Specifically, we transform the online routing problem to a vehicle tour generation problem, and propose a structural graph embedded pointer network to develop these tours iteratively. Furthermore, since constructing supervised training data for the neural network is impractical due to the high computation complexity, we propose a deep reinforcement learning mechanism with an unsupervised auxiliary network to train the model parameters. A multisampling scheme is also devised to further improve the system performance. Since the parameter training process is offline, the proposed strategy can achieve a superior online route generation speed. To assess the proposed strategy, we conduct comprehensive case studies with a real-world transportation network. The simulation results show that the proposed strategy can significantly outperform conventional strategies with limited computation time in both static and dynamic logistic systems. In addition, the influence of control parameters on the system performance is investigated.

Online Vehicle Routing With Neural Combinatorial Optimization and Deep Reinforcement Learning

The intermittency of renewable energy poses challenges on the reliable and economical operations of microgrids. This paper considers a grid-connected microgrid model which consists of a logistics distribution system, where electric vehicles (EVs) depart from the depot, deliver the goods to multiple demand loads, and then, return to the depot. Based on this, this paper studies the coordinated dispatch strategies of EVs to smooth renewable energy and load fluctuations of the microgrid while ensuring the quality of logistics services. A microgrid operation model is proposed to optimize the driving routes, fast-charging time, and regular-charging/discharging strategies of EVs. Specifically, the objective is to minimize the overall operation cost of the microgrid while satisfying the requirements of the logistics distribution tasks. A self-adaptively imperialist competitive algorithm is proposed to solve the model. The simulation results demonstrate the effectiveness of the proposed model.

Operational Planning of Electric Vehicles for Balancing Wind Power and Load Fluctuations in a Microgrid

Lately, the Vehicle Routing Problem (VRP) in the city, known as City VRP, has gained popularity with its importance in city logistics. Similar to city logistics, City VRP mainly differs from conventional VRP in terms of the stakeholders involved, namely the shipper, carrier, resident, and administrator. Accordingly, this paper surveys the City VRP literature categorized by stakeholders and summarizes the constraints, models, and solution methods for VRP in urban cities. City VRPs are also analyzed based on the problem of interest considered by the stakeholders and the corresponding models that have been proposed in response. Through this review, we identify the state of the art of City VRP, highlight the core challenging issues, and suggest some potential research area in this field that have remained underexplored.

Nengsheng Allan Zhang

Papers

City Vehicle Routing Problem (City VRP): A Review