Collaborative optimization for loading operation planning and vessel traffic scheduling in dry bulk ports. (January 2022)
- Record Type:
- Journal Article
- Title:
- Collaborative optimization for loading operation planning and vessel traffic scheduling in dry bulk ports. (January 2022)
- Main Title:
- Collaborative optimization for loading operation planning and vessel traffic scheduling in dry bulk ports
- Authors:
- Zhang, Xinyu
Li, Junjie
Yang, Zaili
Wang, Xinjian - Abstract:
- Highlights: Collaborative optimization of loading operation planning and vessel traffic scheduling was proposed. A multi-objective mixed integer linear programming model was formulated. NSG-II-VNS algorithm was developed to solve the model. The effectiveness of the proposed approaches was verified by numerical experiments. Abstract: While loading operation planning and vessel traffic scheduling are still deemed as two independent operations in practice, it has been realised that their collaborative optimization and coordination can improve port operation efficiency. It is because that two separate operations often result in vessels spending more waiting time when passing through channels and/or longer loading time at berth, and hence seriously affect the productivity and efficiency of ports. It is even worse in the case where multi-harbor basins share a restricted channel. Therefore, this paper aims to address the collaborative optimization of loading operation planning and vessel traffic scheduling (COLOPVTS) and to generate the optimal traffic scheduling scheme and loading operation plan for each vessel synchronously. Through analyzing the process of vessels entering and leaving dry bulk export ports, a multi-objective mathematical model of COLOPVTS is proposed. Due to the complexity of the model, a heuristic algorithm combining the Variable Neighborhood Search (VNS) and Non-dominated Sorting Genetic Algorithm II (NSGA-II) is applied to solve the model. Finally, theHighlights: Collaborative optimization of loading operation planning and vessel traffic scheduling was proposed. A multi-objective mixed integer linear programming model was formulated. NSG-II-VNS algorithm was developed to solve the model. The effectiveness of the proposed approaches was verified by numerical experiments. Abstract: While loading operation planning and vessel traffic scheduling are still deemed as two independent operations in practice, it has been realised that their collaborative optimization and coordination can improve port operation efficiency. It is because that two separate operations often result in vessels spending more waiting time when passing through channels and/or longer loading time at berth, and hence seriously affect the productivity and efficiency of ports. It is even worse in the case where multi-harbor basins share a restricted channel. Therefore, this paper aims to address the collaborative optimization of loading operation planning and vessel traffic scheduling (COLOPVTS) and to generate the optimal traffic scheduling scheme and loading operation plan for each vessel synchronously. Through analyzing the process of vessels entering and leaving dry bulk export ports, a multi-objective mathematical model of COLOPVTS is proposed. Due to the complexity of the model, a heuristic algorithm combining the Variable Neighborhood Search (VNS) and Non-dominated Sorting Genetic Algorithm II (NSGA-II) is applied to solve the model. Finally, the computational results on the practical data of Phase I and Phase II terminals in Huanghua coal port are analysed to verify the rationality and effectiveness of the proposed model and algorithm. … (more)
- Is Part Of:
- Advanced engineering informatics. Volume 51(2022)
- Journal:
- Advanced engineering informatics
- Issue:
- Volume 51(2022)
- Issue Display:
- Volume 51, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 51
- Issue:
- 2022
- Issue Sort Value:
- 2022-0051-2022-0000
- Page Start:
- Page End:
- Publication Date:
- 2022-01
- Subjects:
- Dry bulk port -- Loading operation planning -- Vessel traffic scheduling -- Collaborative optimization -- VNS -- NSGA-II
Computer-aided engineering -- Periodicals
Engineering -- Data processing -- Periodicals
620.00285 - Journal URLs:
- http://www.sciencedirect.com/science/journal/14740346 ↗
http://books.google.com/books?id=KhFVAAAAMAAJ ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.aei.2021.101489 ↗
- Languages:
- English
- ISSNs:
- 1474-0346
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 0696.851100
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 20994.xml