Abstract
Electric vehicles play a key role for developing an eco-sustainable transport system. One critical component of an electric vehicle is its battery, which can be quickly charged or exchanged before it runs out. The problem of electric vehicle dispatching falls into the category of the shortest path problem with resource renewal. In this paper, we study the shortest path problems in (1) electric transit bus scheduling and (2) electric truck routing with time windows. In these applications, a fully-charged battery allows running a limited operational distance, and the battery before depletion needs to be quickly charged or exchanged with a fully-charged one at a battery management facility. The limited distance and battery renewal result in a shortest path problem with resource renewal. We develop a label-correcting algorithm with state space relaxation to find optimal solutions. In the computational experiments, real-world road geometry data are used to generate realistic travel distances, and other types of data are obtained from the real world or randomly generated. The computational results show that the label-correcting algorithm performs very well.
Highlights
Aimed at reducing vehicle emissions and greenhouse gases, more and more electric transit buses and delivery trucks have been used in personal travel, public transit, home deliveries from grocery stores, postal deliveries and courier services
The problem of electric vehicle dispatching with battery renewal falls into the category of the resource-constrained shortest path problem
We model the shortest path problem in two important applications: (1) electric transit bus scheduling and (2) electric truck routing with time windows
Summary
Aimed at reducing vehicle emissions and greenhouse gases, more and more electric transit buses and delivery trucks have been used in personal travel, public transit, home deliveries from grocery stores, postal deliveries and courier services. Solution methods are mainly based on dynamic programming with the strategies of two-cycle elimination [5,17], k-cycle elimination [18] and a combined (k, 2)-loop elimination [19] Both types of resource-constrained shortest path problems are NP-hard [20]. We consider the shortest path problems in two types of electric vehicles with battery renewal: electric buses and electric trucks. The problem on electric buses is defined as follows: given an origin and a destination depot, a set of scheduled trips with starting and ending times, the travel distance between two locations, the maximal range of the electric bus before battery renewal and the cost between two nodes, find the shortest path from the origin depot to the destination depot.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
