{"data":{"id":"10.6084/m9.figshare.6992063.v1","type":"dois","attributes":{"doi":"10.6084/m9.figshare.6992063.v1","prefix":"10.6084","suffix":"m9.figshare.6992063.v1","identifiers":[],"alternateIdentifiers":[],"creators":[{"name":"Facchini, Francesco","nameType":"Personal","givenName":"Francesco","familyName":"Facchini","affiliation":[],"nameIdentifiers":[]},{"name":"Boenzi, Francesco","nameType":"Personal","givenName":"Francesco","familyName":"Boenzi","affiliation":[],"nameIdentifiers":[]},{"name":"Digiesi, Salvatore","nameType":"Personal","givenName":"Salvatore","familyName":"Digiesi","affiliation":[],"nameIdentifiers":[]},{"name":"Mummolo, Giovanni","nameType":"Personal","givenName":"Giovanni","familyName":"Mummolo","affiliation":[],"nameIdentifiers":[]}],"titles":[{"title":"A model-based Decision Support System for multiple container terminals hub management"}],"publisher":"SciELO journals","container":{},"publicationYear":2018,"subjects":[{"subject":"91099 Manufacturing Engineering not elsewhere classified","subjectScheme":"FOR"},{"subject":"FOS: Electrical engineering, electronic engineering, information engineering","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Electrical engineering, electronic engineering, information engineering","subjectScheme":"Fields of Science and Technology (FOS)"}],"contributors":[],"dates":[{"date":"2018-08-22","dateType":"Created"},{"date":"2018-08-22","dateType":"Updated"},{"date":"2018","dateType":"Issued"}],"language":null,"types":{"ris":"DATA","bibtex":"misc","citeproc":"dataset","schemaOrg":"Dataset","resourceType":"Dataset","resourceTypeGeneral":"Dataset"},"relatedIdentifiers":[{"relationType":"IsSupplementTo","relatedIdentifier":"10.1590/0103-6513.20170074","relatedIdentifierType":"DOI"},{"relationType":"IsIdenticalTo","relatedIdentifier":"10.6084/m9.figshare.6992063","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":["655227 Bytes"],"formats":[],"version":null,"rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"Abstract Paper aims To develop a model-based Decision Support System (DSS) that allows identifying the best strategy of the inter-/intra-terminal flows of the containers in order to increasing the performance of the hub under economic and environmental perspective. Originality The adoption of a dry port can effectively solve the congestion problem of a terminal only if an integrated sustainable solution (dry port location and container strategy storage) is identified. Research method The model is based on a heuristic computational algorithm for non-linear programming. Main findings The application of DSS to a full-scale numerical case show the model capabilities in identifying the optimal logistic strategies ensuring a low CF and in optimizing the cost due to transport activities. Implications for theory and practice It is possible to identify different strategies allowing to obtain an eco-friendly solution reducing, at same time, the costs for a given number of containers to be 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