Proceedings of the 2012 International Conference on Computer Application and System Modeling (ICCASM 2012)

Genetic Algorithm for Dynamic Berth Allocation Problem with Discrete Layout

Authors
Shan Tong
Corresponding Author
Shan Tong
Available Online August 2012.
DOI
10.2991/iccasm.2012.65How to use a DOI?
Keywords
Genetic algorithm,Berth Allocation Problem, Optimization model, Container transportation
Abstract

Genetic Algorithm which is based on the Darwinian principle of natural selection has been successfully applied to Berth allocation problem (BAP), which can decide the ships’ berthing position and berthing time at a container terminal. Considering the service priority, handing time deciding variables, safety clearance, as well as the berths’ physical conditions, a dynamic berth allocation with discrete layout optimization model aimed at minimizing the total service time with the ships service priority considered at the port is proposed, and a genetic algorithm is applied to solve it. Numerical experiment is conducted and shows that the genetic algorithm performs well, and is useful to the container terminal management and can save a lot of resources.

Copyright
© 2012, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2012 International Conference on Computer Application and System Modeling (ICCASM 2012)
Series
Advances in Intelligent Systems Research
Publication Date
August 2012
ISBN
978-94-91216-00-8
ISSN
1951-6851
DOI
10.2991/iccasm.2012.65How to use a DOI?
Copyright
© 2012, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Shan Tong
PY  - 2012/08
DA  - 2012/08
TI  - Genetic Algorithm for Dynamic Berth Allocation Problem with Discrete Layout
BT  - Proceedings of the 2012 International Conference on Computer Application and System Modeling (ICCASM 2012)
PB  - Atlantis Press
SP  - 261
EP  - 264
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccasm.2012.65
DO  - 10.2991/iccasm.2012.65
ID  - Tong2012/08
ER  -