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dc.contributor.authorKrimi, Issam
dc.contributor.authorTodosijević, Raca
dc.contributor.authorBenmansour, Rachid
dc.contributor.authorRatli, Mustapha
dc.contributor.authorETAL.
dc.date.accessioned2022-07-06T05:59:20Z
dc.date.available2022-07-06T05:59:20Z
dc.date.issued2020-03
dc.identifier.citationKrimi, I., Todosijević, R., Benmansour, R. et al. Modelling and solving the multi-quays berth allocation and crane assignment problem with availability constraints. J Glob Optim 78, 349–373 (2020)en_US
dc.identifier.urihttps://dspace.adu.ac.ae/handle/1/3881
dc.description.abstractIn this work, we are interested in the multi-quays berth allocation and crane assignment problem under availability restrictions. Availability restrictions may arise due weather conditions, or when, for example, cranes must undergo planned maintenance in order to stay in good performance. This problem was inspired by a real-case of a bulk port in Morocco. To solve the problem we propose at first a mixed-integer programming model. Then, in view of the limitations of the proposed model, we investigate a set of heuristics based on general variable neighborhood search with three variants of variable neighborhood descent as a local search. To validate the proposed model and the proposed heuristic approach, real-world instances are used. The computational results reveal that CPLEX MIP solver consumes a lot of CPU time to solve this model, even sometimes failing to guarantee the optimality of the provided solution. On the other hand, the proposed GVNS heuristic turns out to be very efficient in solving the considered problem.en_US
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.subjectMulti-quayen_US
dc.subjectBerth allocationen_US
dc.subjectCrane assignmenten_US
dc.subjectBulk portsen_US
dc.subjectAvailability constraintsen_US
dc.subjectVariable Neighborhood Searchen_US
dc.titleModelling and solving the multi-quays berth allocation and crane assignment problem with availability constraintsen_US
dc.title.alternativeJournal of Global Optimizationen_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.1007/s10898-020-00884-1


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