Intelligent Scheduling on Electric Vehicle Routing Problem with Simultaneous Pickup and Delivery
- DOI
- 10.2991/978-94-6463-040-4_174How to use a DOI?
- Keywords
- intelligent scheduling; electric vehicle routing problem; simultaneous pickup and delivery; load-dependent discharging; adaptive large neighbourhood search; commercial software CPLEX
- Abstract
In this paper, we use intelligent scheduling technique to propose an electric vehicle routing problem with simultaneous pickup and delivery (EVRPSPD) model which considers the load-dependent discharging (LD). The model aims to minimize the working time including travel time, charging time, service time, and waiting time. In small-scale problems, rational routing decisions can be obtained directly using the commercial software CPLEX. In addition, we propose an adaptive large neighbourhood search algorithm (ALNS) for this problem, which can solve large-scale problems and obtain feasible solutions in an acceptable amount of time. Our computational investigation indicates that load-dependent discharging is non-negligible for the problem.
- 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 - Wei Xu AU - Ming Cheng PY - 2022 DA - 2022/12/27 TI - Intelligent Scheduling on Electric Vehicle Routing Problem with Simultaneous Pickup and Delivery BT - Proceedings of the 2022 3rd International Conference on Artificial Intelligence and Education (IC-ICAIE 2022) PB - Atlantis Press SP - 1168 EP - 1174 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-040-4_174 DO - 10.2991/978-94-6463-040-4_174 ID - Xu2022 ER -