Abstract
The logistics in ports and maritime supply chains has reached a degree of complexity, that the management of supply chain operations requires of analytical methods to support with objectivity the decision-making process. For practical reasons, these analytical methods need to be embedded into technological platforms in the form of Decision Support Systems (DSS), in order to facilitate the required computations. Several DSS have been developed to address a variety of supply chain operational problems in the port and maritime industry. However, most of them set aside the fundamental discussion on which technological and analytical components are the most suitable for a particular problem. The purpose of this chapter is to survey the literature on the design and development of DSS for the port and maritime industry. We systematically review the works on existing methods (analytical and technological), and distinguish the gaps and tendencies of future developments in this industrial domain. We believe that the following DSS in the context of maritime transport will take advantage of the theoretical development of collaborative systems, data analytics and robustness to ease decision making process in the port and maritime industry. Implications to DSS developers for port and maritime supply chains are discussed.
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Acknowledgements
This research was supported by the PRODEP program of the Mexican Minister of Education (SEP), through the Research Grants DSA/103.5/15/14164 (Research Network on Supply Chain Modeling and Optimization) and DSA/103.5/16/15436 (Postdoctoral Research Fund). The author of this chapter acknowledges the valuable comments of the referees to improve the quality of our work.
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Mar-Ortiz, J., Gracia, M.D., Castillo-García, N. (2018). Challenges in the Design of Decision Support Systems for Port and Maritime Supply Chains. In: Valencia-García, R., Paredes-Valverde, M., Salas-Zárate, M., Alor-Hernández, G. (eds) Exploring Intelligent Decision Support Systems. Studies in Computational Intelligence, vol 764. Springer, Cham. https://doi.org/10.1007/978-3-319-74002-7_3
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