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2019 | OriginalPaper | Buchkapitel

Realization of ETA Predictions for Intermodal Logistics Networks Using Artificial Intelligence

verfasst von : Peter Poschmann, Manuel Weinke, Andreas Balster, Frank Straube, Hanno Friedrich, André Ludwig

Erschienen in: Advances in Production, Logistics and Traffic

Verlag: Springer International Publishing

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Abstract

Intermodal logistics networks such as the maritime transport chain require a precise interaction of numerous actors. However, due to their complexity, the closely interlinked processes are highly susceptible to disruptions. Companies are constantly faced with the challenge of dealing effectively and efficiently with disruptions and resultant delays. At the same time, they are confronted with increasing logistical requirements related to higher quality and flexibility demands of customers (Straube et al. 2013). Supply chains are becoming increasingly vulnerable, due to the associated necessity to cope with increasing volatility while simultaneously reducing risk buffers in processes as a result of rising cost pressure. Combined with ongoing changes due to digitization, this situation contributes significantly to an increasing need for improved information transparency among companies and their customers.

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Literatur
Zurück zum Zitat Büker, T., Seybold, B.: Stochastic modelling of delay propagation in large networks. J. Rail Transp. Plan. Manag. 2(1–2), 34–50 (2012) Büker, T., Seybold, B.: Stochastic modelling of delay propagation in large networks. J. Rail Transp. Plan. Manag. 2(1–2), 34–50 (2012)
Zurück zum Zitat Chang, H., Park, D., Lee, S., Lee, H., Baek, S.: Dynamic multi-interval bus travel time prediction using bus transit data. Transportmetrica 6(1), 19–38 (2010)CrossRef Chang, H., Park, D., Lee, S., Lee, H., Baek, S.: Dynamic multi-interval bus travel time prediction using bus transit data. Transportmetrica 6(1), 19–38 (2010)CrossRef
Zurück zum Zitat Goverde, R.M.: A delay propagation algorithm for large-scale railway traffic networks. Transp. Res. Part C Emerg. Technol. 18(3), 269–287 (2010)CrossRef Goverde, R.M.: A delay propagation algorithm for large-scale railway traffic networks. Transp. Res. Part C Emerg. Technol. 18(3), 269–287 (2010)CrossRef
Zurück zum Zitat Holderied, C.: Güterverkehr, Spedition und Logistik. Oldenbourg, München (2005)CrossRef Holderied, C.: Güterverkehr, Spedition und Logistik. Oldenbourg, München (2005)CrossRef
Zurück zum Zitat Markovic, N., Milinkovic, S., Tikhonov, K.S., Schonfeld, P.: Analyzing passenger train arrival delays with support vector regression. Transp. Res. Part C Emerg. Technol. 56, 251–262 (2015)CrossRef Markovic, N., Milinkovic, S., Tikhonov, K.S., Schonfeld, P.: Analyzing passenger train arrival delays with support vector regression. Transp. Res. Part C Emerg. Technol. 56, 251–262 (2015)CrossRef
Zurück zum Zitat Nash, A., Huerlimann, D.: Railroad simulation using OpenTrack. Comput. Railw. 9, 45–59 (2004) Nash, A., Huerlimann, D.: Railroad simulation using OpenTrack. Comput. Railw. 9, 45–59 (2004)
Zurück zum Zitat Özekici, S., Sengör, S.: On a rail transportation model with scheduled services. Transp. Sci. 28(3), 246–255 (1994)CrossRef Özekici, S., Sengör, S.: On a rail transportation model with scheduled services. Transp. Sci. 28(3), 246–255 (1994)CrossRef
Zurück zum Zitat Radtke, A., Hauptmann, D.: Automated planning of timetables in large railway networks using a microscopic data basis and railway simulation techniques. Comput. Railw. 9, 615–625 (2004) Radtke, A., Hauptmann, D.: Automated planning of timetables in large railway networks using a microscopic data basis and railway simulation techniques. Comput. Railw. 9, 615–625 (2004)
Zurück zum Zitat Straube, F., Handfield, R., Pfohl, H.C., Wieland, A.: Trends und Strategien in Logistik und Supply Chain Management. DVV Media Group, Hamburg (2013) Straube, F., Handfield, R., Pfohl, H.C., Wieland, A.: Trends und Strategien in Logistik und Supply Chain Management. DVV Media Group, Hamburg (2013)
Zurück zum Zitat Walter, F.: Informationsaustausch in der maritimen Transportkette. Springer Gabler (2016) Walter, F.: Informationsaustausch in der maritimen Transportkette. Springer Gabler (2016)
Zurück zum Zitat Van Riessen, B., Negenborn, R.R., Dekker, R.: Real-time container transport planning with decision trees based on offline obtained optimal solutions. Decis. Support Syst. 89, 1–16 (2016)CrossRef Van Riessen, B., Negenborn, R.R., Dekker, R.: Real-time container transport planning with decision trees based on offline obtained optimal solutions. Decis. Support Syst. 89, 1–16 (2016)CrossRef
Zurück zum Zitat Yaghini, M., Khoshraftar, M.M., Seyedabadi, M.: Railway passenger train delay prediction via neural network model. J. Adv. Transp. 47(3), 355–368 (2013)CrossRef Yaghini, M., Khoshraftar, M.M., Seyedabadi, M.: Railway passenger train delay prediction via neural network model. J. Adv. Transp. 47(3), 355–368 (2013)CrossRef
Zurück zum Zitat Zegordi, S.H., Davarzani, H.: Developing a supply chain disruption analysis model: application of colored Petri-nets. Expert Syst. Appl. 39(2), 2101–2111 (2012)CrossRef Zegordi, S.H., Davarzani, H.: Developing a supply chain disruption analysis model: application of colored Petri-nets. Expert Syst. Appl. 39(2), 2101–2111 (2012)CrossRef
Zurück zum Zitat Zhang, J., Teixeira, A.P., Soares, C.G., Yan, X., Liu, K.: Maritime transportation risk assessment of Tianjin port with Bayesian belief networks. Risk Anal. 36(6), 1171–1187 (2016)CrossRef Zhang, J., Teixeira, A.P., Soares, C.G., Yan, X., Liu, K.: Maritime transportation risk assessment of Tianjin port with Bayesian belief networks. Risk Anal. 36(6), 1171–1187 (2016)CrossRef
Metadaten
Titel
Realization of ETA Predictions for Intermodal Logistics Networks Using Artificial Intelligence
verfasst von
Peter Poschmann
Manuel Weinke
Andreas Balster
Frank Straube
Hanno Friedrich
André Ludwig
Copyright-Jahr
2019
DOI
https://doi.org/10.1007/978-3-030-13535-5_12