Modelling of integrated vehicle scheduling and container storage problems in unloading process at an automated container terminal

Jiabin Luo; Y. Wu; A. Bergsten Mendes

doi:10.1016/j.cie.2016.01.010

Modelling of integrated vehicle scheduling and container storage problems in unloading process at an automated container terminal

Jiabin Luo, Y. Wu, A. Bergsten Mendes

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80 Citations (Scopus)

203 Downloads (Pure)

Abstract

Effectively scheduling vehicles and allocating storage locations for containers are two important problems in container terminal operations. Early research efforts, however, are devoted to study them separately. This paper investigates the integration of the two problems focusing on the unloading process in an automated container terminal, where all or part of the equipment are built in automation. We formulate the integrated problem as a mixed-integer programming (MIP) model to minimise ship’s berth time. We determine the detailed schedules for all vehicles to be used during the unloading process and the storage location to be assigned for all containers. A series of experiments are carried out for small-sized problems by using commercial software. A genetic algorithm (GA) is designed for solving large-sized problems. The solutions from the GA for the small-sized problems are compared with the optimal solutions obtained from the commercial software to verify the effectiveness of the GA. The computational results show that the model and solution methods proposed in this paper are efficient in solving the integrated unloading problem for the automated container terminal.

Original language	English
Pages (from-to)	32-44
Journal	Computers & Industrial Engineering
Volume	94
DOIs	https://doi.org/10.1016/j.cie.2016.01.010
Publication status	Published - 23 Jan 2016

Bibliographical note

NOTICE: this is the author’s version of a work that was accepted for publication in Computers and Industrial Engineering. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computers and Industrial Engineering, [94, (2016)] DOI: 10.1016/j.cie.2016.01.010

© 2016, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/

Keywords

Integer programming
Automated container terminal
Vehicle scheduling
Container storage
Container unloading

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Cite this

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title = "Modelling of integrated vehicle scheduling and container storage problems in unloading process at an automated container terminal",

abstract = "Effectively scheduling vehicles and allocating storage locations for containers are two important problems in container terminal operations. Early research efforts, however, are devoted to study them separately. This paper investigates the integration of the two problems focusing on the unloading process in an automated container terminal, where all or part of the equipment are built in automation. We formulate the integrated problem as a mixed-integer programming (MIP) model to minimise ship{\textquoteright}s berth time. We determine the detailed schedules for all vehicles to be used during the unloading process and the storage location to be assigned for all containers. A series of experiments are carried out for small-sized problems by using commercial software. A genetic algorithm (GA) is designed for solving large-sized problems. The solutions from the GA for the small-sized problems are compared with the optimal solutions obtained from the commercial software to verify the effectiveness of the GA. The computational results show that the model and solution methods proposed in this paper are efficient in solving the integrated unloading problem for the automated container terminal.",

keywords = "Integer programming, Automated container terminal, Vehicle scheduling, Container storage, Container unloading",

author = "Jiabin Luo and Y. Wu and {Bergsten Mendes}, A.",

note = "NOTICE: this is the author{\textquoteright}s version of a work that was accepted for publication in Computers and Industrial Engineering. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computers and Industrial Engineering, [94, (2016)] DOI: 10.1016/j.cie.2016.01.010 {\textcopyright} 2016, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ ",

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AU - Luo, Jiabin

AU - Wu, Y.

AU - Bergsten Mendes, A.

N1 - NOTICE: this is the author’s version of a work that was accepted for publication in Computers and Industrial Engineering. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computers and Industrial Engineering, [94, (2016)] DOI: 10.1016/j.cie.2016.01.010 © 2016, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/

PY - 2016/1/23

Y1 - 2016/1/23

N2 - Effectively scheduling vehicles and allocating storage locations for containers are two important problems in container terminal operations. Early research efforts, however, are devoted to study them separately. This paper investigates the integration of the two problems focusing on the unloading process in an automated container terminal, where all or part of the equipment are built in automation. We formulate the integrated problem as a mixed-integer programming (MIP) model to minimise ship’s berth time. We determine the detailed schedules for all vehicles to be used during the unloading process and the storage location to be assigned for all containers. A series of experiments are carried out for small-sized problems by using commercial software. A genetic algorithm (GA) is designed for solving large-sized problems. The solutions from the GA for the small-sized problems are compared with the optimal solutions obtained from the commercial software to verify the effectiveness of the GA. The computational results show that the model and solution methods proposed in this paper are efficient in solving the integrated unloading problem for the automated container terminal.

AB - Effectively scheduling vehicles and allocating storage locations for containers are two important problems in container terminal operations. Early research efforts, however, are devoted to study them separately. This paper investigates the integration of the two problems focusing on the unloading process in an automated container terminal, where all or part of the equipment are built in automation. We formulate the integrated problem as a mixed-integer programming (MIP) model to minimise ship’s berth time. We determine the detailed schedules for all vehicles to be used during the unloading process and the storage location to be assigned for all containers. A series of experiments are carried out for small-sized problems by using commercial software. A genetic algorithm (GA) is designed for solving large-sized problems. The solutions from the GA for the small-sized problems are compared with the optimal solutions obtained from the commercial software to verify the effectiveness of the GA. The computational results show that the model and solution methods proposed in this paper are efficient in solving the integrated unloading problem for the automated container terminal.

KW - Integer programming

KW - Automated container terminal

KW - Vehicle scheduling

KW - Container storage

KW - Container unloading

U2 - 10.1016/j.cie.2016.01.010

DO - 10.1016/j.cie.2016.01.010

M3 - Article

VL - 94

SP - 32

EP - 44

JO - Computers & Industrial Engineering

JF - Computers & Industrial Engineering

ER -

Modelling of integrated vehicle scheduling and container storage problems in unloading process at an automated container terminal

Abstract

Bibliographical note

Keywords

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