In recent years, maritime freight transportation and the consequent handling of containers are among the most dynamic and growing sectors. The aim of this research is to propose a Decision Support System (DSS) addressed mainly to shipping companies, allowing the choice, even en-route, of the hub port of destination for the successive multi-modal operations. The companies make choices in relation both to the ship location and to a dynamic accessibility indicator. The accessibility indicator is generally accepted as the parameter that better represents the interactions between a port and its hinterland. Different factors can influence the accessibility in maritime transport; some of them are characterized by low variability, while others show a high within-day dynamics. For example, the technical characteristics of ports (number of berths and their depths, number of cranes, storage area, etc.) belong to the first group; instead, the number of free berths, the delay time in freight loading and unloading operations, and weather conditions can change during the day. Their variability can be evaluated by a real-time monitoring, while the ship location can be easily obtained by GPS and radar signals. In the proposed DSS, we have considered data about the technical characteristics of ports and, depending on the request coming from ships, acquires the dynamic characteristics of each port, the ship location and the destination area. After the completion of the process, the DSS provides as output the port “closer” to the requests expressed by the users. Since some current values of both the dynamic characteristics of ports and information provided by shipping companies are subject to uncertainty, we proposed a DSS based on a multivariate accessibility indicator.


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    Title :

    A multivariate logic decision support system for optimization of the maritime routes


    Contributors:


    Publication date :

    2017-06-01


    Size :

    277522 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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