The impact of clustered, dynamic and stochastic estimated time of arrival forecasts on the pre-and post-haulage of intermodal transport Problem instances
| dc.contributor.author | Rentschler, Johannes | |
| dc.date.accessioned | 2024-04-02T11:51:25Z | |
| dc.date.available | 2024-04-02T11:51:25Z | |
| dc.date.issued | 2024-04-02 | |
| dc.identifier.uri | https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/4198 | |
| dc.identifier.uri | https://doi.org/10.48328/tudatalib-1402 | |
| dc.description | This data set contains the problem instances for the dynamic and stochastic Pick-up and Delivery Problem with Time Windows and clustered release dates (PDPTW-crd) from the working paper "The impact of clustered, dynamic and stochastic estimated time of arrival forecasts on the pre-and post-haulage of intermodal transport – a simulation study". | de_DE |
| dc.rights | Creative Commons Attribution 4.0 | |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
| dc.subject.classification | 1.24-05 Operations Management und BWL-spezifische Wirtschaftsinformatik | de_DE |
| dc.subject.classification | 4.41-04 Verkehrs- und Transportsysteme, Intelligenter und automatisierter Verkehr | de_DE |
| dc.subject.ddc | 650 | |
| dc.subject.ddc | 380 | |
| dc.title | The impact of clustered, dynamic and stochastic estimated time of arrival forecasts on the pre-and post-haulage of intermodal transport Problem instances | de_DE |
| dc.type | Dataset | de_DE |
| tud.unit | TUDa | |
| tud.history.classification | Version=2020-2024;112-03 Betriebswirtschaftslehre | |
| tud.history.classification | Version=2020-2024;407-04 Verkehrs- und Transportsysteme, Intelligenter und automatisierter Verkehr |
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