A multi-objective evolutionary algorithm for berth allocation in a container port

Cheong, CY; Lin, CJ; Tan, KC; Liu, DK

A multi-objective evolutionary algorithm for berth allocation in a container port

Cheong, CY Lin, CJ Tan, KC Liu, DK

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Publication Type:: Conference Proceeding
Citation:: 2007 IEEE Congress on Evolutionary Computation, CEC 2007, 2007, pp. 927 - 934
Issue Date:: 2007-12-01

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Field	Value	Language
dc.contributor.author	Cheong, CY	en_US
dc.contributor.author	Lin, CJ	en_US
dc.contributor.author	Tan, KC	en_US
dc.contributor.author	Liu, DK https://orcid.org/0000-0002-1581-5582	en_US
dc.date.issued	2007-12-01	en_US
dc.identifier.citation	2007 IEEE Congress on Evolutionary Computation, CEC 2007, 2007, pp. 927 - 934	en_US
dc.identifier.isbn	1424413400	en_US
dc.identifier.isbn	9781424413409	en_US
dc.identifier.uri	http://hdl.handle.net/10453/2371
dc.description.abstract	This paper considers a berth allocation problem (BAP) which requires the determination of exact berthing times and positions of incoming ships in a container port. The problem is solved by optimizing the berth schedule so as to minimize concurrently the three objectives of make span, number of crossings, and waiting time. These objectives represent the interests of both port and ship operators. A multi-objective evolutionary algorithm (MOEA) that incorporates the concept of Pareto optimality is proposed for solving the multi-objective BAP. The MOEA is equipped with a novel solution decoding scheme which is specifically designed to optimize the use of berth space. The MOEA is also able to function in a dynamic context which is of more relevance to a real-world situation. © 2007 IEEE.	en_US
dc.relation.ispartof	2007 IEEE Congress on Evolutionary Computation, CEC 2007	en_US
dc.relation.isbasedon	10.1109/CEC.2007.4424569	en_US
dc.title	A multi-objective evolutionary algorithm for berth allocation in a container port	en_US
dc.type	Conference Proceeding
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
dc.location.activity	Singapore	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CAS - Centre for Autonomous Systems
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

This paper considers a berth allocation problem (BAP) which requires the determination of exact berthing times and positions of incoming ships in a container port. The problem is solved by optimizing the berth schedule so as to minimize concurrently the three objectives of make span, number of crossings, and waiting time. These objectives represent the interests of both port and ship operators. A multi-objective evolutionary algorithm (MOEA) that incorporates the concept of Pareto optimality is proposed for solving the multi-objective BAP. The MOEA is equipped with a novel solution decoding scheme which is specifically designed to optimize the use of berth space. The MOEA is also able to function in a dynamic context which is of more relevance to a real-world situation. © 2007 IEEE.

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http://hdl.handle.net/10453/2371