Machine Learning-Based Optimization Models for Defining Storage Rules in Maritime Container Yards

This paper proposes an integrated approach to define the best consignment strategy for storing containers in an export yard of a maritime terminal. The storage strategy identifies the rules for grouping homogeneous containers, which are defined simultaneously with the assignment of each group of con...

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書誌詳細

主要な著者:	Daniela Ambrosino, Haoqi Xie
フォーマット:	Artigo
言語:	Inglês
出版事項:	MDPI AG 2024-11-01
シリーズ:	Modelling
主題:	maritime container terminal yard management stacking and storage strategies spectral clustering integer linear programming
オンライン･アクセス:	https://www.mdpi.com/2673-3951/5/4/85
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