The seaport service rate prediction system: Using drayage truck trajectory data to predict seaport service rates

Citation data:

Decision Support Systems, ISSN: 0167-9236, Vol: 95, Page: 37-48

Publication Year:
2017
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DOI:
10.1016/j.dss.2016.11.008
Author(s):
Meditya Wasesa, Andries Stam, Eric van Heck
Publisher(s):
Elsevier BV
Tags:
Business, Management and Accounting, Computer Science, Psychology, Arts and Humanities, Decision Sciences
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article description
For drayage operators the service rate of seaports is crucial for organizing their container pick-up/delivery operations. This study presents a seaport service rate prediction system that could help drayage operators to improve their predictions of the duration of the pick-up/delivery operations at a seaport by using the subordinate trucks' trajectory data. The system is constructed based on three components namely, trajectory reconstruction, geo-fencing analysis, and gradient boosting modelling. Using predictive analytic techniques, the prediction system is trained and validated using more than 15 million data records from over 200 trucks over a period of 19 months. The gradient boosting model-based solution provides better predictions compared with the linear model benchmark solution. Conclusions and implications are formulated.

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