Rolling horizon based robust optimization method of quayside operations in maritime container ports. (15th July 2022)
- Record Type:
- Journal Article
- Title:
- Rolling horizon based robust optimization method of quayside operations in maritime container ports. (15th July 2022)
- Main Title:
- Rolling horizon based robust optimization method of quayside operations in maritime container ports
- Authors:
- Liu, Wenqian
Zhu, Xiaoning
Wang, Li
Li, Siqiao - Abstract:
- Abstract: The quayside operation is a complex system in maritime shipping, which requires an intelligent scheduling approach to cope with complex situations. This paper investigates joint berth allocation and quay crane assignment problem considering uncertain arrival time of vessels and operation efficiency of quay cranes. A nominal model of this problem considering vessel priorities is presented firstly. Meanwhile, a multi-objective robust model is built based on the idea of robust optimization. Besides, control parameters are introduced into the model for levels of uncertainties. Then, an intelligent search algorithm integrated with rolling horizon is designed for solving the problem. Finally, the model and proposed approach are validated by computational results with different instance sizes. Results point out that intelligent algorithm is superior on solution quality and solving time for large-scale examples. Besides, vessel delays show obvious impact on the scheme than uncertain quay crane productivity, especially under the medium uncertainty level. Highlights: A joint berth allocation and quay crane assignment robust model with uncertain factors is presented. The uncertainties of vessel arriving times and crane efficiency are measured by control parameters. An intelligent scheduling approach is integrated with rolling horizon. The anti-interference capability of scheme is enhanced with proactive strategy. The medium uncertainty level shows obvious impact on initialAbstract: The quayside operation is a complex system in maritime shipping, which requires an intelligent scheduling approach to cope with complex situations. This paper investigates joint berth allocation and quay crane assignment problem considering uncertain arrival time of vessels and operation efficiency of quay cranes. A nominal model of this problem considering vessel priorities is presented firstly. Meanwhile, a multi-objective robust model is built based on the idea of robust optimization. Besides, control parameters are introduced into the model for levels of uncertainties. Then, an intelligent search algorithm integrated with rolling horizon is designed for solving the problem. Finally, the model and proposed approach are validated by computational results with different instance sizes. Results point out that intelligent algorithm is superior on solution quality and solving time for large-scale examples. Besides, vessel delays show obvious impact on the scheme than uncertain quay crane productivity, especially under the medium uncertainty level. Highlights: A joint berth allocation and quay crane assignment robust model with uncertain factors is presented. The uncertainties of vessel arriving times and crane efficiency are measured by control parameters. An intelligent scheduling approach is integrated with rolling horizon. The anti-interference capability of scheme is enhanced with proactive strategy. The medium uncertainty level shows obvious impact on initial operation scheme. … (more)
- Is Part Of:
- Ocean engineering. Volume 256(2022)
- Journal:
- Ocean engineering
- Issue:
- Volume 256(2022)
- Issue Display:
- Volume 256, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 256
- Issue:
- 2022
- Issue Sort Value:
- 2022-0256-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-07-15
- Subjects:
- Maritime container terminal -- Berth allocation problem -- Quay crane assignment problem -- Robust strategy -- Uncertain situations -- Adaptive large neighborhood search
Ocean engineering -- Periodicals
Ocean engineering
Periodicals
620.4162 - Journal URLs:
- http://www.sciencedirect.com/science/journal/00298018 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.oceaneng.2022.111505 ↗
- Languages:
- English
- ISSNs:
- 0029-8018
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6231.280000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 21555.xml