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Forecasting of short-term flow freight congestion: A study case of Algeciras Bay Port (Spain)

Ruiz Aguilar, Juan Jesús and Turias, Ignacio J. and Moscoso López, José A. and Jiménez Come, María J. and Cerbán, María M. (2016) Forecasting of short-term flow freight congestion: A study case of Algeciras Bay Port (Spain). DYNA, 83 (195). pp. 163-172. ISSN 2346-2183

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Resumen

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.

Tipo de documento:Artículo - Article
Palabras clave:freight forecasting, classification, congestion, artificial neural networks, multiple comparison tests
Temática:6 Tecnología (ciencias aplicadas) / Technology > 62 Ingeniería y operaciones afines / Engineering
Unidad administrativa:Revistas electrónicas UN > Dyna
Código ID:58920
Enviado por : Dirección Nacional de Bibliotecas STECNICO
Enviado el día :31 Oct 2017 17:20
Ultima modificación:27 Noviembre 2017 22:05
Ultima modificación:27 Noviembre 2017 22:05
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