Abstract
Technological innovation has been reshaping all walks of life, and the marine shipping industry is no exception. Autonomous vessels have gained significant attention due to their numerous advantages. However, regulatory constraints and expensive manufacturing costs are impeding the application of autonomous vessels. To overcome these challenges, this research conducts experiments with autonomous ships on national waterways with less regulation and develops a model to investigate their impact on shipping company operations. The model simultaneously optimizes ship routing, fleet sizing, fleet deployment, and demand fulfillment, taking into account demand uncertainty. Two solution methods, i.e., sample average approximation and a two-phase Benders-based branch-and-cut algorithm, are proposed to solve the problem with acceleration strategies, including column generation and variable fixing. The performance of several solution techniques is tested through numerical experiments using real-world data. Besides, sensitivity analyses are conducted to further discuss the influence of key factors and derive constructive managerial insights for shipping companies.
| Original language | English |
|---|---|
| Article number | 102851 |
| Number of pages | 22 |
| Journal | Transportation Research Part B: Methodological |
| Volume | 178 |
| Early online date | 2 Nov 2023 |
| DOIs | |
| Publication status | Published - 31 Dec 2023 |
Bibliographical note
Acknowledgements:This work was supported by the National Natural Science Foundation of China [Grant Nos. 72071173, 71831008, 72025103, 72361137001], and the Research Grants Council of the Hong Kong Special Administrative Region, China [Project number HKSAR RGC TRS T32-707/22-N].
Data availability:
Data will be made available on request.
Keywords
- Autonomous ship
- shipping company operations
- sample average approximation
- branch-and-cut
- Benders decomposition;
