Real-time disruption management approach for intermodal freight transportation
| Autor: | Martin Hrušovský, Tom Van Woensel, Werner Jammernegg, Emrah Demir |
|---|---|
| Přispěvatelé: | Operations Planning Acc. & Control, EAISI Mobility |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Decision support system
Computer science 020209 energy Strategy and Management 02 engineering and technology SDG 9 – Industrie Industrial and Manufacturing Engineering Disruption management 0202 electrical engineering electronic engineering information engineering Innovation Reliability (statistics) 0505 law General Environmental Science Simulation optimization Real-time planning Intermodal freight transportation Disruption management Simulation-optimization Renewable Energy Sustainability and the Environment 05 social sciences innovatie en infrastructuur Flow network Unexpected events Sustainable transport Risk analysis (engineering) 050501 criminology and Infrastructure SDG 9 - Industry Innovation and Infrastructure SDG 9 - Industry Externality |
| Zdroj: | Journal of Cleaner Production, 280(Part 2):124826. Elsevier |
| ISSN: | 0959-6526 |
| Popis: | The share of intermodal transportation, which is often considered as a sustainable transportation alternative, is rather low compared to road transportation. There are several reasons for this situation, including the increased need for coordination of scheduled transport services and the reduced reliability of intermodal transport chains in case of disruptions. In this regard, developing an advanced algorithmic approach can help to handle real-time data during the execution of transportation and react adequately to detected unexpected events. In this way the reliability of intermodal transport can be increased, which might help to increase its usage and to minimize the negative externalities of freight transportation. This paper proposes a novel real-time decision support system based on a hybrid simulation-optimization approach for intermodal transportation which combines offline planning with online re-planning based on real-time data about unexpected events in the transportation network. For each detected disruption, the affected services and orders are identified and the best re-planning policy is applied. The proposed decision support system is successfully tested on real-life scenarios and is capable of delivering fast and reasonably good solutions in an online environment. This research might be of particular benefit to the transport industry for using advanced solution methodologies and give advice to transportation planners about the optimal policies that can be used in case of disruptions. |
| Databáze: | OpenAIRE |
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