- Title
- An efficient multi-vehicle routing strategy for goods delivery services
- Creator
- Le, Duy; Men, Ying; Luo, Yunkang; Zhou, Yixuan; Nguyen, Linh
- Date
- 2021
- Type
- Text; Conference paper
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/180280
- Identifier
- vital:15736
- Identifier
-
https://doi.org/10.1109/ARSO51874.2021.9541547
- Identifier
- ISBN:2162-7568 (ISSN); 9781665449533 (ISBN)
- Abstract
- The paper addresses the problem of efficiently planning routes for multiple ground vehicles used in goods delivery services. Given popularity of today's e-commerce, particularly under the COVID-19 pandemic conditions, goods delivery services have been booming than ever, dominated by small-scaled (electric) bikes and promised by autonomous vehicles. However, finding optimal routing paths for multiple delivery vehicles operating simultaneously in order to minimize transportation cost is a fundamental but challenging problem. In this paper, it is first proposed to exploit the mixed integer programming paradigm to model the delivery routing optimization problem (DROP) for multiple simultaneously-operating vehicles given their energy constraints. The routing optimization problem is then solved by the multi-chromosome genetic algorithm, where the number of delivery vehicles can be optimized. The proposed approach was evaluated in a realworld experiment in which goods were expected to be delivered from a depot to 26 suburb locations in Canberra, Australia. The obtained results demonstrate effectiveness of the proposed algorithm. © 2021 IEEE.
- Publisher
- IEEE Computer Society
- Relation
- 2021 IEEE International Conference on Advanced Robotics and Its Social Impacts, ARSO 2021 Vol. 2021-July, p. 188-193
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Rights
- Copyright @ 2021 IEEE
- Reviewed
- Hits: 793
- Visitors: 758
- Downloads: 0
| Thumbnail | File | Description | Size | Format |
|---|