<abstract xmlns="http://www.w3.org/1999/xhtml"><p>This paper investigates the use of neural networks (NNs) for the problem of assigning push boats to barge convoys in inland waterway transportation (IWT). Push boat–barge convoy assignmentsare part of the daily decision-making process done by dispatchers in IWT companiesforwhich a decision support tool does not exist. The aim of this paper is to develop a Neural Network Ensemble (NNE) model that will be able to assist in push boat–barge convoy assignments based on the push boat power.The primary objective of this paper is to derive an NNE model for calculation of push boat Shaft Powers (SHPs) by using less than 100% of the experimental data available. The NNE model is applied to a real-world case of more than one shipping company from the Republic of Serbia, which is encountered on the Danube River. The solution obtained from the NNE model is compared toreal-world full-scale speed/power measurements carried out on Serbian push boats, as well as with the results obtained from the previous NNE model. It is found that the model is highly accurate, with scope for further improvements.</p></abstract>

This paper investigates the use of neural networks (NNs) for the problem of assigning push boats to barge convoys in inland waterway transportation (IWT). Push boat–barge convoy assignmentsare part of the daily decision-making process done by dispatchers in IWT companiesforwhich a decision support tool does not exist. The aim of this paper is to develop a Neural Network Ensemble (NNE) model that will be able to assist in push boat–barge convoy assignments based on the push boat power.The primary objective of this paper is to derive an NNE model for calculation of push boat Shaft Powers (SHPs) by using less than 100% of the experimental data available. The NNE model is applied to a real-world case of more than one shipping company from the Republic of Serbia, which is encountered on the Danube River. The solution obtained from the NNE model is compared toreal-world full-scale speed/power measurements carried out on Serbian push boats, as well as with the results obtained from the previous NNE model. It is found that the model is highly accurate, with scope for further improvements.

Neural Network Ensemble Approach to Pushed Convoys Dispatching Problems

Faculty of Transport and Traffic Engineering

Polish Maritime Research

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

{"article-title":"Neural Network Ensemble Approach to Pushed Convoys Dispatching Problems"}

This paper investigates the use of neural networks (NNs) for the problem of assigning push boats to barge convoys in inland waterway transportation (IWT). Push...

Neural Network Ensemble Approach to Pushed Convoys Dispatching Problems

Publié en ligne: 30 avr. 2020

Pages: 70 - 82

DOI: https://doi.org/10.2478/pomr-2020-0008

Mots clés
Neural Network Ensembles, push boat, inland waterway transportation, full-scale speed/power trials

© 2020 Aleksandar Radonjić et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Neural Network Ensemble Approach to Pushed Convoys Dispatching Problems

Publié en ligne: 30 avr. 2020

Pages: 70 - 82

DOI: https://doi.org/10.2478/pomr-2020-0008

Mots clésNeural Network Ensembles, push boat, inland waterway transportation, full-scale speed/power trials

© 2020 Aleksandar Radonjić et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Mots clés
Neural Network Ensembles, push boat, inland waterway transportation, full-scale speed/power trials