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Please use this identifier to cite or link to this item: http://hdl.handle.net/10651/36673

Title: A genetic algorithm for robust berth allocation and quay crane assignment
Author(s): Rodríguez Molins, Mario
Ingolotti, Laura
Barber, Federico
Salido, Miguel A.
Sierra Sánchez, María Rita
Puente Peinador, Jorge
Keywords: Scheduling
Genetic algorithms
Issue date: Jul-2014
Publisher: Springer
Publisher version: http://dx.doi.org/10.1007/s13748-014-0056-3
Citation: Progress in Artificial Intelligence, 2(4), p. 177-192 (2014); doi:10.1007/s13748-014-0056-3
Format extent: p. 177-192
Abstract: Scheduling problems usually obtain the optimal solutions assuming that the environment is deterministic. However, actually the environment is dynamic and uncertain. Thus, the initial data could change and the initial schedule obtained might be unfeasible. To overcome this issue, a proactive approach is presented for scheduling problems without any previous knowledge about the incidences that can occur. In this paper, we consider the berth allocation problem and the quay crane assignment problem as a representative example of scheduling problems where a typical objective is to minimize the service time. The robustness is introduced within this problem by means of buffer times that should be maximized to absorb possible incidences or breakdowns. Therefore, this problem becomes a multi-objective optimization problem with two opposite objectives: minimizing the total service time and maximizing the robustness or buffer times
URI: http://hdl.handle.net/10651/36673
ISSN: 2192-6352
Sponsored: This research was supported by the Spanish Government under research projects TIN2010-20976-C02-01 and TIN2010-20976-C02-02 (Min. de Ciencia e Innovación, Spain), the project PIRSES-GA-2011-294931 (FP7-PEOPLE-2011-IRSES) and the predoctoral FPU fellowship (AP2010-4405)
Project id.: MEC/TIN2010-20976-C02
PIRSES-GA-2011-294931 (FP7-PEOPLE-2011-IRSES)
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