Author:
Expósito-Izquierdo Christopher,Lalla-Ruiz Eduardo,Melian-Batista, Belén,Moreno-Vega J. Marcos
Abstract
Providing a suitable answer to different types of unforeseen changes in optimization problems is one challenging goal. This paper addresses the Quay Crane Scheduling Problem under random disruptions, whose goal is to determine the sequences of transshipment operations performed by a set of quay cranes in order to load and unload containers onto/from a berthed container vessel. An evolutionary algorithm is used to find an initial solution of the problem with completely deterministic data, whereas several rescheduling strategies are integrated into a dynamism management system aimed at keeping a proper quality level after a random disruption. Computational experiments indicate that using knowledge about previous static problems can largely improve the performance of the implemented schedule.
Publisher
IBERAMIA: Sociedad Iberoamericana de Inteligencia Artificial
Subject
Artificial Intelligence,Software
Cited by
5 articles.
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