Solving the berth allocation problem with service priority via multi-objective optimization

Cheong, CY; Tan, KC; Liu, DK

Solving the berth allocation problem with service priority via multi-objective optimization

Cheong, CY Tan, KC Liu, DK

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Publication Type:: Conference Proceeding
Citation:: 2009 IEEE Symposium on Computational Intelligence in Scheduling, CI-Sched 2009 - Proceedings, 2009, pp. 95 - 102
Issue Date:: 2009-07-20

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Field	Value	Language
dc.contributor.author	Cheong, CY	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	2009-07-20	en_US
dc.identifier.citation	2009 IEEE Symposium on Computational Intelligence in Scheduling, CI-Sched 2009 - Proceedings, 2009, pp. 95 - 102	en_US
dc.identifier.isbn	9781424427574	en_US
dc.identifier.uri	http://hdl.handle.net/10453/11974
dc.description.abstract	This paper studies a multi-objective instance of the berth allocation problem (BAP). The BAP involves the determination of exact berthing times and positions of incoming ships in a container port so as to minimize concurrently the three objectives of makespan of the port, total waiting time of the ships, and degree of deviation from a predetermined service priority schedule. These objectives represent the interests of both port and ship operators. Unlike most existing approaches in the literature which are singleobjective- based, a multi-objective evolutionary algorithm (MOEA) that incorporates the concept of Pareto optimality is proposed for solving the multi-objective BAP. The multiobjective approach reveals several interesting characteristics of the BAP.	en_US
dc.relation.ispartof	2009 IEEE Symposium on Computational Intelligence in Scheduling, CI-Sched 2009 - Proceedings	en_US
dc.relation.isbasedon	10.1109/SCIS.2009.4927021	en_US
dc.title	Solving the berth allocation problem with service priority via multi-objective optimization	en_US
dc.type	Conference Proceeding
utslib.for	0910 Manufacturing Engineering	en_US
dc.location.activity	Sheraton Music City Hotel, Nashville, TN, USA	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 studies a multi-objective instance of the berth allocation problem (BAP). The BAP involves the determination of exact berthing times and positions of incoming ships in a container port so as to minimize concurrently the three objectives of makespan of the port, total waiting time of the ships, and degree of deviation from a predetermined service priority schedule. These objectives represent the interests of both port and ship operators. Unlike most existing approaches in the literature which are singleobjective- based, a multi-objective evolutionary algorithm (MOEA) that incorporates the concept of Pareto optimality is proposed for solving the multi-objective BAP. The multiobjective approach reveals several interesting characteristics of the BAP.

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http://hdl.handle.net/10453/11974