Multi-Objective Electric Vehicle Route and Charging Planning with Contraction Hierarchies
Keywords: Contraction Hierarchies, Multi-objective, Charging cost, Route planning, Charging planning, Electric vehicle
TL;DR: Practically usable multi-objective EV route and charging planning algorithm on realistic instances
Abstract: Electric vehicle (EV) travel planning is a complex task that involves planning the routes and the charging sessions for EVs while optimizing travel duration and cost. We show the applicability of the multi-objective EV travel planning algorithm with practically usable solution times on country-sized road graphs with a large number of charging stations and a realistic EV model. The approach is based on multi-objective A* search enhanced by Contraction hierarchies, optimal dimensionality reduction, and sub-optimal $\epsilon$-relaxation techniques. We performed an extensive empirical evaluation on 182\,000 problem instances showing the impact of various algorithm settings on real-world map of Bavaria and Germany with more than 12\,000 charging stations. The results show the proposed approach is the first one capable of performing such a genuine multi-objective optimization on realistically large country-scale problem instances that can achieve practically usable planning times in order of seconds with only a minor loss of solution quality.
The achieved speed-up varies from $\sim11\times$ for optimal solution to more than $250\times$ for sub-optimal solution compared to vanilla multi-objective A*.
Primary Keywords: Applications
Category: Long
Student: Graduate
Submission Number: 232
Loading