期刊名称：Inteligencia Artificial : Ibero-American Journal of Artificial Intelligence
印刷版ISSN：1137-3601
电子版ISSN：1988-3064
出版年度：2014
卷号：17
期号：54
页码：35-47
语种：English
出版社：Spanish Association for Intelligence Artificial
摘要：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.
