A Survey on Artificial Intelligence based Methods for Locating Hubs in Transport Networks

Abstract

The location of hubs in transport networks constitutes one of the key elements affecting the organization of freight and passengers’ transport logistics activities. This work offers a good literature review of implementing artificial intelligence (AI) methods in identifying hubs of such networks. In this research study, the author examines different categories of AI techniques such as machine learning techniques, innovative neural structures, and optimization techniques to understand how those technologies could be useful for the improvement of hub location techniques. The given survey offers the comparison of various AI techniques and encourages potential applicants for showing on real transport circumstances where different sorts of AI let in the construction of good consequences. Unlike most prior papers in the context of AI-based hub location, this research contributes not only a literature review of theories but also discussion about data needs, algorithms, and interfaces with the current transport systems. Based on the analysis of the results of the latest studies and the definition of new trends related to the use of AI, this survey will also be useful for researchers and practitioners who are interested in the application of AI in the effective management of transport networks. From the findings of this study, the following lessons are anticipated to support advancement in stronger, cheaper and more convenient transport solutions that will improve accessibility and increase economic recovery.