Forecasting of short-term flow freight congestion: A study case of Algeciras Bay Port (Spain)
The prediction of freight congestion (cargo peaks) is an important tool for decision making and it is this paper’s main object of study. Forecasting freight flows can be a useful tool for the whole logistics chain. In this work, a complete methodology is presented in order to obtain the best model t...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Universidad Nacional de Colombia
2016-01-01
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| Series: | Dyna |
| Subjects: | |
| Online Access: | https://revistas.unal.edu.co/index.php/dyna/article/view/47027 |
| _version_ | 1818755570180554752 |
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| author | Juan Jesús Ruiz Aguilar Ignacio J. Turias José A. Moscoso López María J. Jiménez Come María M. Cerbán |
| author_facet | Juan Jesús Ruiz Aguilar Ignacio J. Turias José A. Moscoso López María J. Jiménez Come María M. Cerbán |
| author_sort | Juan Jesús Ruiz Aguilar |
| collection | DOAJ |
| description | The prediction of freight congestion (cargo peaks) is an important tool for decision making and it is this paper’s main object of study. Forecasting freight flows can be a useful tool for the whole logistics chain. In this work, a complete methodology is presented in order to obtain the best model to predict freight congestion situations at ports. The prediction is modeled as a classification problem and different approaches are tested (k-Nearest Neighbors, Bayes classifier and Artificial Neural Networks). A panel of different experts (post–hoc methods of Friedman test) has been developed in order to select the best model. The proposed methodology is applied in the Strait of Gibraltar’s logistics hub with a study case being undertaken in Port of Algeciras Bay. The results obtained reveal the efficiency of the presented models that can be applied to improve daily operations planning. |
| first_indexed | 2024-12-18T05:41:15Z |
| format | Article |
| id | doaj.art-8933022bdfbc42db8bfd2aad3c3007ca |
| institution | Directory Open Access Journal |
| issn | 0012-7353 2346-2183 |
| language | English |
| last_indexed | 2024-12-18T05:41:15Z |
| publishDate | 2016-01-01 |
| publisher | Universidad Nacional de Colombia |
| record_format | Article |
| series | Dyna |
| spelling | doaj.art-8933022bdfbc42db8bfd2aad3c3007ca2022-12-21T21:19:11ZengUniversidad Nacional de ColombiaDyna0012-73532346-21832016-01-018319516317210.15446/dyna.v83n195.4702742504Forecasting of short-term flow freight congestion: A study case of Algeciras Bay Port (Spain)Juan Jesús Ruiz Aguilar0Ignacio J. Turias1José A. Moscoso López2María J. Jiménez Come3María M. Cerbán4Universidad de CádizUniversidad de CádizUniversidad de CádizUniversidad de CádizUniversidad de CádizThe prediction of freight congestion (cargo peaks) is an important tool for decision making and it is this paper’s main object of study. Forecasting freight flows can be a useful tool for the whole logistics chain. In this work, a complete methodology is presented in order to obtain the best model to predict freight congestion situations at ports. The prediction is modeled as a classification problem and different approaches are tested (k-Nearest Neighbors, Bayes classifier and Artificial Neural Networks). A panel of different experts (post–hoc methods of Friedman test) has been developed in order to select the best model. The proposed methodology is applied in the Strait of Gibraltar’s logistics hub with a study case being undertaken in Port of Algeciras Bay. The results obtained reveal the efficiency of the presented models that can be applied to improve daily operations planning.https://revistas.unal.edu.co/index.php/dyna/article/view/47027freight forecastingclassificationcongestionartificial neural networksmultiple comparison tests |
| spellingShingle | Juan Jesús Ruiz Aguilar Ignacio J. Turias José A. Moscoso López María J. Jiménez Come María M. Cerbán Forecasting of short-term flow freight congestion: A study case of Algeciras Bay Port (Spain) Dyna freight forecasting classification congestion artificial neural networks multiple comparison tests |
| title | Forecasting of short-term flow freight congestion: A study case of Algeciras Bay Port (Spain) |
| title_full | Forecasting of short-term flow freight congestion: A study case of Algeciras Bay Port (Spain) |
| title_fullStr | Forecasting of short-term flow freight congestion: A study case of Algeciras Bay Port (Spain) |
| title_full_unstemmed | Forecasting of short-term flow freight congestion: A study case of Algeciras Bay Port (Spain) |
| title_short | Forecasting of short-term flow freight congestion: A study case of Algeciras Bay Port (Spain) |
| title_sort | forecasting of short term flow freight congestion a study case of algeciras bay port spain |
| topic | freight forecasting classification congestion artificial neural networks multiple comparison tests |
| url | https://revistas.unal.edu.co/index.php/dyna/article/view/47027 |
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