The Seaport Service Rate Prediction System: Using Drayage Truck Trajectory Data to Predict Seaport Service Rates

Meditya Wasesa*, Andries Stam, Eric van Heck

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

28 Citations (Scopus)

Abstract

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.
Original languageEnglish
Pages (from-to)37-48
Number of pages12
JournalDecision Support Systems
Volume95
Issue numberMarch
DOIs
Publication statusPublished - Mar 2017

Research programs

  • RSM LIS

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