Scheduling inland waterway transport vessels and locks using a switching max-plus-linear systems approach
This paper considers the inland waterborne transport (IWT) problem, and presents a scheduling approach for inland vessels and locks to generate optimal vessel and lock timetables. The scheduling strategy is designed in the switching max-plus-linear (SMPL) systems framework, as these are characterize...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2022 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/404429 |
| Acceso en línea: | https://hdl.handle.net/2117/404429 https://dx.doi.org/10.1109/OJITS.2022.3218334 |
| Access Level: | acceso abierto |
| Palabra clave: | Predictive control Waterways Inland navigation Inland waterborne transport Intelligent transportation systems Vessel-to-infrastructure interaction Scheduling Max-plus algebra Switching max-plus-linear systems Control predictiu Transport fluvial Navegació interior Àrees temàtiques de la UPC::Informàtica::Automàtica i control |
| Sumario: | This paper considers the inland waterborne transport (IWT) problem, and presents a scheduling approach for inland vessels and locks to generate optimal vessel and lock timetables. The scheduling strategy is designed in the switching max-plus-linear (SMPL) systems framework, as these are characterized by a number of features that make them well suited to represent the IWT problem. In particular, the resulting model is linear in the max-plus algebra, and SMPL systems can switch between modes, an interesting feature due to the presence of vessel routing and ordering constraints in the model. Moreover, SMPL systems can be transformed into mixed-integer linear programming (MILP) problems, for which efficient solvers are available. Finally, a realistic case study is used to test the approach and assess its effectiveness. |
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