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Supporting Operational and Real-time Planning Tasks of Road Freight Transport with Machine Learning. Guiding the Implementation of Machine Learning Algorithms
Advances in Information Systems and Management Science, Bd. 69
Sandra Lechtenberg
ISBN 978-3-8325-5630-3
349 Seiten, Erscheinungsjahr: 2023
Preis: 50.00 €
Supporting Operational and Real-time Planning Tasks of Road Freight Transport with Machine Learning. Guiding the Implementation of Machine Learning Algorithms
World-wide trends such as globalization, demographic shifts, increased customer demands, and shorter product lifecycles present a significant challenge to the road freight transport industry: meeting the growing road freight transport demand economically while striving for sustainability. Artificial intelligence, particularly machine learning, is expected to empower transport planners to incorporate more information and react quicker to the fast-changing decision environment. Hence, using machine learning can lead to more efficient and effective transport planning. However, despite the promising prospects of machine learning in road freight transport planning, both academia and industry struggle to identify and implement suitable use cases to gain a competitive edge.
In her dissertation, Sandra Lechtenberg explores how machine learning can enhance decision-making in operational and real-time road freight transport planning. She outlines an implementation guideline, which involves identifying decision tasks in planning processes, assessing their suitability for machine learning, and proposing steps to follow when implementing respective algorithms.
Leseprobe (PDF)
Keywords:
- Machine Learning
- Artificial Intelligence
- Road Freight
- Transport Planning
- Digital Transformation
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