Research on the distribution problem of electric logistics vehicle based on quantum whale algorithm considering charging strategy
- DOI
- 10.2991/978-94-6463-102-9_87How to use a DOI?
- Keywords
- Electric logistics vehicles; Route planning; Hybrid charging mode; Quantum whale algorithm
- Abstract
With the continuous introduction of national carbon emission reduction policies, especially in the field of logistics and distribution, the use of electric vehicles can effectively reduce carbon emissions and the key factors are charging mode and time window constraints and the choice of charging piles, so this paper constructs an electric logistics vehicle distribution model that considers factors such as electric logistics vehicle charging mode and customer time window according to actual needs. In order to improve the problem that the traditional whale swarm algorithm has a low solution speed and is easy to fall into the local optimal solution, this paper uses the Grover quantum algorithm for quantum acceleration, and uses the variable neighborhood search algorithm to perform a variety of neighborhood searches, so that the algorithm can effectively jump out of the local optimal solution and obtain the global optimal solution. Finally, a study is used to verify the rationality of the model and the effectiveness of the algorithm.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Yue Yan PY - 2022 DA - 2022/12/29 TI - Research on the distribution problem of electric logistics vehicle based on quantum whale algorithm considering charging strategy BT - Proceedings of the 2022 2nd International Conference on Business Administration and Data Science (BADS 2022) PB - Atlantis Press SP - 847 EP - 854 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-102-9_87 DO - 10.2991/978-94-6463-102-9_87 ID - Yan2022 ER -