A Machine Learning-based system for berth scheduling at bulk terminals

作者：

Highlights：

• Novel machine learning-based system for supporting berthing operations in bulk ports.

• The system recommends the best algorithm in most of the studied cases.

• Different meta-features for the berth allocation problem are investigated.

• The system exhibits a relevant robustness when tackling new and unfamiliar scenarios.

摘要

•Novel machine learning-based system for supporting berthing operations in bulk ports.•The system recommends the best algorithm in most of the studied cases.•Different meta-features for the berth allocation problem are investigated.•The system exhibits a relevant robustness when tackling new and unfamiliar scenarios.

论文关键词：Berth allocation problem,Bulk transportation,Machine-learning,Machine-learning,Meta-learning,Decision support

论文评审过程：Received 21 February 2017, Revised 6 June 2017, Accepted 7 June 2017, Available online 10 June 2017, Version of Record 20 June 2017.

论文官网地址：https://doi.org/10.1016/j.eswa.2017.06.010