English

Optimal routing algorithm for trips involving thousands of ev-charging stations using Kinetica-Graph

Distributed, Parallel, and Cluster Computing 2022-06-14 v1 Optimization and Control

Abstract

This paper discusses a graph based route solving algorithm to find the optimal path for an electric vehicle picking the best charging locations among thousands to minimize the total cumulative driving distance between the end points of the trip. To this end, we have devised a combinatorial optimization algorithm and a fixed storage graph topology construction for the graph road network of the continental USA. We have also re-purposed our existing Dijkstra solver to reduce the computational cost of many shortest path solves involved in the algorithm. An adaptive and light weight spatial search structure is also devised for finding a set of prospective stations at each charging location using uniform bins and double link associations. The entire algorithm is implemented as yet another multi-threaded at-scale graph solver within the suite of Kinetica-Graph analytics, exposed as a restful API endpoint and operable within SQL. Several example trips are solved and the results are demonstrated within the context.

Keywords

Cite

@article{arxiv.2206.06241,
  title  = {Optimal routing algorithm for trips involving thousands of ev-charging stations using Kinetica-Graph},
  author = {B. Kaan Karamete and Eli Glaser},
  journal= {arXiv preprint arXiv:2206.06241},
  year   = {2022}
}

Comments

13 pages, 15 figures, 13 references

R2 v1 2026-06-24T11:49:13.641Z