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Logistics 2018, 2(1), 5; https://doi.org/10.3390/logistics2010005

Use of Bayesian Networks to Analyze Port Variables in Order to Make Sustainable Planning and Management Decision

1
Departamento de Ingeniería Civil, Transportes, Universidad Politécnica de Madrid, 28040 Madrid, Spain
2
Departamento Tessella-Altran World Class Center for Analytics, Altran Innovación, 28022 Madrid, Spain
3
Departamento de Ingeniería Civil, Universidad Europea de Madrid, Madrid 28670, Spain
*
Author to whom correspondence should be addressed.
Received: 26 October 2017 / Revised: 12 December 2017 / Accepted: 13 December 2017 / Published: 11 January 2018
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Abstract

In the current economic, social and political environment, society demands a greater variety of outcomes from the public logistics sector, such as efficiency, efficiency of managed resources, greater transparency and business performance. All of them are an indispensable counterpart for its recognition and support. In case of port planning and management, many variables are included. Use of Bayesian Networks allows to classify, predict and diagnose these variables and even to estimate the subsequent probability of unknown variables, basing on the known ones. Research includes a data base with more than 40 variables, which have been classified as smart port studies in Spain. Then a network was generated using a non-cyclic conducted grafo, which shows port variable relationships. As conclusion, economic variables are cause of the rest of categories and they represent a parent role in the most of cases. Furthermore, if environmental variables are known, subsequent probability of social variables can be estimated. View Full-Text
Keywords: Bayesian Networks; graph theory; sustainability; port management; artificial networks Bayesian Networks; graph theory; sustainability; port management; artificial networks
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Molina Serrano, B.; González-Cancelas, N.; Soler-Flores, F.; Awad-Nuñez, S.; Camarero Orive, A. Use of Bayesian Networks to Analyze Port Variables in Order to Make Sustainable Planning and Management Decision. Logistics 2018, 2, 5.

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