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A cooperative search for berth scheduling

Published online by Cambridge University Press:  18 January 2017

Eduardo Lalla-Ruiz ,
Belén Melián-Batista Open the ORCID record for Belén Melián-Batista [Opens in a new window]  and
José Marcos Moreno-Vega Open the ORCID record for José Marcos Moreno-Vega [Opens in a new window]
Eduardo Lalla-Ruiz
Affiliation:
Department of Computer Engineering and Systems, University of La Laguna, 38271-La Laguna, Spain e-mail: elalla@ull.es, mbmelia@ull.es, jmmoreno@ull.es
Belén Melián-Batista
Affiliation:
Department of Computer Engineering and Systems, University of La Laguna, 38271-La Laguna, Spain e-mail: elalla@ull.es, mbmelia@ull.es, jmmoreno@ull.es
José Marcos Moreno-Vega
Affiliation:
Department of Computer Engineering and Systems, University of La Laguna, 38271-La Laguna, Spain e-mail: elalla@ull.es, mbmelia@ull.es, jmmoreno@ull.es
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Abstract

With the growing demand of freight transport by means of container vessels as well as the important competition among terminals, managers and stakeholders seek to improve the exploitation of the container terminal resources efficiently. In this context, arises the Berth Allocation Problem, which aims to allocate and schedule incoming vessels along the quay. Its appropriate solution plays a relevant role in enhancing the terminal productivity. Thus, for addressing this problem, we propose a cooperative search, where the individuals are organized into groups and each member shares information with its group partners. This grouping strategy allows to diversify as well as intensify the search in some regions by means of information shared among the individuals of each group. The computational experiments for this problem reveal that our approach reports high-quality solutions and identifies promising regions within the search space in short computational times.

Type
Articles
Information
The Knowledge Engineering Review , Volume 31 , Special Issue 5: Constraint Satisfaction for Planning and Scheduling , November 2016 , pp. 498 - 507
Copyright
© Cambridge University Press, 2017 

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