Обзорная статья

Utilizing machine learning on freight transportation and logistics applications: A review

Kalliopi TsolakiCentre for Research and Technology Hellas, Information Technologies Institute, 57001 Thessaloniki, GreeceThanasis VafeiadisCentre for Research and Technology Hellas, Information Technologies Institute, 57001 Thessaloniki, GreeceAlexandros NizamisCentre for Research and Technology Hellas, Information Technologies Institute, 57001 Thessaloniki, GreeceDimosthenis IoannidisCentre for Research and Technology Hellas, Information Technologies Institute, 57001 Thessaloniki, GreeceDimitrios TzovarasCentre for Research and Technology Hellas, Information Technologies Institute, 57001 Thessaloniki, Greece

2022en

ABI

Аннотация

This review article explores and locates the current state-of-the-art related to application areas from freight transportation, supply chain and logistics that focuses on arrival time, demand forecasting, industrial processes optimization, traffic flow and location prediction, the vehicle routing problem and anomaly detection on transportation data. This review categorizes the related works according to machine learning methodologies so as to present the methods’ evolution through time, their combinations and their connection with the various applications in the specified fields. Thus, a reader would effortlessly get insights about the current state-of-the-art related to machine learning in freight transportation and related application areas.

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Идентификаторы

DOI: 10.1016/j.icte.2022.02.001

Цитирования и источники

Цитирований: 5Использованных источников: 0

Показатели — AkademScholar