Project description
This project proposes as its main objective the creation and implementation of an intelligent route management system composed of more than one driver based on a set of en route exchange points where the system, based on simulations with data extracted from the fleet of Padrosa Management SL and the state of the European road system in real time, It seeks the optimization of these interchange points in order to minimize the time of each transport and maximize the optimal interaction between routes. In addition, the project seeks not only to improve the efficiency of transport operations but also to optimize the management and use of data related to these processes. The project is distinguished by its holistic approach to logistics problems, from the creation of a generator of exchange points by route and a unified data manager to the analysis of data that help the company in making decisions based on data in real time. This project will apply the most avant-garde techniques in digital simulation, such as digital twins, and heterogeneous data management, characteristic of the logistics sector.
In the current landscape of the logistics sector, characterized by incipient digitalization and a still limited use of data, a unique opportunity for transformation and innovation is emerging. Padrosa Management SL, one of the most outstanding Catalan companies in the country in this sector, has positioned itself as a leader in the search for new ways to improve operational efficiency and strategic management. In this context, this proposal for an industrial doctorate arises, the result of collaboration between the UPC's IDEAI research group and Padrosa Management SL.
The heart of the project lies in the development of an exchange point generator that uses advanced algorithms and detailed data to identify the most efficient routes, thus reducing costs and transport times. This tool is intended to be integrated into the logistics systems already existing in the company. At the same time, the project foresees the creation of a data manager. This system will seek a scalable, secure and compatible design with different types and data sources, allowing real-time analysis and extraction of valuable knowledge that can be used for continuous improvement and adaptation to new needs and business opportunities.
The academic work associated with this PhD includes the writing and publication of several scientific articles documenting the technical developments, methodological processes, performance evaluations and practical implications of the systems developed.
Bibliography:
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Monique Stinson, Joshua Auld, Abolfazl (Kouros) Mohammadian, A large-scale, agent-based simulation of metropolitan freight movements with passenger and freight market interactions, Procedia Computer Science, https://doi.org/10.1016/j.procs.2020.03.157.
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Goldsman, David & Pernet, Sebastien & Kang, Keebom. (2002). Logistics 1: simulation of transportation logistics.. 901-904. 10.1145/1030453.1030580.
Liu, Yushan, Bailan He, Marcel Hildebrandt, Maximilian Buchner, Daniela Inzko, Roger Wernert, Emanuel Weigel, Dagmar Beyer, Martin Berbalk, and Volker Tresp. 2023. "A Knowledge Graph Perspective on Supply Chain Resilience." arXiv preprint arXiv:2305.08506.
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Barrasa, Jesus, and Jim Webber. Building Knowledge Graphs. 1st ed. O'Reilly Media, 2023. ISBN 9781098127077.
