{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T10:17:50Z","timestamp":1778753870136,"version":"3.51.4"},"reference-count":38,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2022,11,28]],"date-time":"2022-11-28T00:00:00Z","timestamp":1669593600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>A real problem of today\u2019s society is the loss of human lives due to road accidents and the pollution caused by freight transport through metropolitan areas. The restrictions imposed in the near future for freight transport could reduce its efficiency and create many more problems. Using data centralization and developing applications or algorithms dedicated to the freight transportation sectors, routes and emissions can be managed much more efficiently. In this work, general aspects are presented, as well as a route optimization model for freight transport, taking into account the environmental impact, based on a heuristic algorithm, that of the ant colony (ACO). A multitude of studies has focused on what represents the benefits created by the applicability of solutions rather than on generalities and perspectives. The paper aims to highlight the usefulness of an optimization model of freight transport routes and the minimization of time and social costs. The study will show us that an optimized route for freight transport has a huge impact on costs, but also on time efficiency and polluting emissions.<\/jats:p>","DOI":"10.3390\/s22239255","type":"journal-article","created":{"date-parts":[[2022,11,28]],"date-time":"2022-11-28T09:09:42Z","timestamp":1669626582000},"page":"9255","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Applied Study of the Fluidization Model of Logistics Transportation through the Prism of the Impact Generated on the Environment"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6378-7670","authenticated-orcid":false,"given":"Eduard","family":"Zadobrischi","sequence":"first","affiliation":[{"name":"Department of Computers, Electronics and Automation, Faculty of Electrical Engineering and Computer Science, \u201cStefan cel Mare\u201d University, No.13. Str. Universitatii, 720229 Suceava, Romania"},{"name":"Department of Computer Science, Technical University of Cluj-Napoca, Gh. Baritiu St. 26-28, 400027 Cluj-Napoca, Romania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8039-8415","authenticated-orcid":false,"given":"Mihai","family":"Negru","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Technical University of Cluj-Napoca, Gh. Baritiu St. 26-28, 400027 Cluj-Napoca, Romania"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,11,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Zadobrischi, E. (2022). Intelligent traffic monitoring through heterogeneous and autonomous networks dedicated to traffic automation. Sensors, 22.","DOI":"10.3390\/s22207861"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Zadobrischi, E., and Dimian, M. (2021). 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