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Improving Transportation Planning Using Machine Learning
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Author(s): Satish Vadlamani (Kenco Management Services, LLC, USA)and Mayank Modashiya (Kenco Management Services, LLC, USA)
Copyright: 2023
Pages: 13
Source title:
Encyclopedia of Data Science and Machine Learning
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
DOI: 10.4018/978-1-7998-9220-5.ch184
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Abstract
Supply chains are complex and continuously evolving to become more complex. With globalization of supply chains and ever-increasing customer demands for better service, planning is very important. The vulnerabilities in the supply chain were exposed with COVID-19, and transportation, a key supply chain element, was impacted significantly. Transportation connects various nodes in the supply chain network. There are several nodes, numerous links between nodes, various modes of transportation in addition to people and systems in the network. Ensuring better service for customers is of paramount importance for companies. With disparate systems involved, collecting and harnessing this data can identify problems in the network. Data science techniques, machine learning, and artificial intelligence can help identify service failures in planning even before they happen. Predicting service failures in planning can ensure better service and reduce costs. In this article, the authors use machine learning to predict service failures in domestic transportation planning.
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