Priority rules for handling containers to improve energy consumption and terminal efficiency

Abstract This paper addresses the optimization of the yard crane handling processes in a container terminal to reduce energy consumption and improve overall system performance. More precisely, the paper presents and evaluates different sequencing rules, based on predefined priorities, to organize the rail yard to minimize moves during the rail loading operations. The minimization of overall energy consumption and maximum tardiness are considered, simultaneously assessing these two components of the objective function to better understand how they interact and how they can be optimized together. As a novel issue in optimization, a hill climbing algorithm is implemented, searching for the yard configuration that most improves the efficiency of container handling while being able to integrate different management rules of the terminal. The reference case study is the PSA Pra terminal in Genoa, Italy. A full rail yard with known delivery times, and crane operating along a single stack, is the operative scenario. Random due time sequences are generated during test instances, while technical data of crane are used. Moreover, crane movements involve both loading and unloading along multiple axes. From the results, the best priority rules improve energy consumption and lateness of the initial configuration of the yard by up to 55%, thus allowing the terminal management to reorganize the storage areas accordingly and improve their efficiency. The proposed priority rules bridge the gap between theoretical optimization procedures and container terminal practices.

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Publication Details

Journal
Maritime Economics & Logistics
Published
2024-09-03
DOI
https://doi.org/10.1057/s41278-024-00302-3
Citations
2
Primary Topic
Maritime Ports and Logistics
Type
article
Field-Weighted Citation Impact
0.70

Funders

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article

Priority rules for handling containers to improve energy consumption and terminal efficiency

Anna Sciomachen, Alessia Giulianetti
2 citations
Maritime Economics & Logistics
Maritime Ports and Logistics
0.70
article

Priority rules for handling containers to improve energy consumption and terminal efficiency

Anna Sciomachen, Alessia Giulianetti
article en
2 citations

Abstract

Abstract This paper addresses the optimization of the yard crane handling processes in a container terminal to reduce energy consumption and improve overall system performance. More precisely, the paper presents and evaluates different sequencing rules, based on predefined priorities, to organize the rail yard to minimize moves during the rail loading operations. The minimization of overall energy consumption and maximum tardiness are considered, simultaneously assessing these two components of the objective function to better understand how they interact and how they can be optimized together. As a novel issue in optimization, a hill climbing algorithm is implemented, searching for the yard configuration that most improves the efficiency of container handling while being able to integrate different management rules of the terminal. The reference case study is the PSA Pra terminal in Genoa, Italy. A full rail yard with known delivery times, and crane operating along a single stack, is the operative scenario. Random due time sequences are generated during test instances, while technical data of crane are used. Moreover, crane movements involve both loading and unloading along multiple axes. From the results, the best priority rules improve energy consumption and lateness of the initial configuration of the yard by up to 55%, thus allowing the terminal management to reorganize the storage areas accordingly and improve their efficiency. The proposed priority rules bridge the gap between theoretical optimization procedures and container terminal practices.

Maritime Economics & LogisticsVol. 27(3)
University of Genoa (IT)
European Commission, Università degli Studi di Genova
Affordable and clean energy
Openalex Percentile: Top 26%
Maritime Ports and Logistics
0.70
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