Containership Load Planning with Crane Operations

dc.contributor.advisorHaghani, Alien_US
dc.contributor.authorHamedi, Masouden_US
dc.contributor.departmentCivil Engineeringen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2011-07-06T05:59:30Z
dc.date.available2011-07-06T05:59:30Z
dc.date.issued2011en_US
dc.description.abstractSince the start of the containerization revolution in 1950's, not only the TEU capacity of the vessels has been increasing constantly, but also the number of fully cellular container ships has expanded substantially. Because of the tense competition among ports in recent years, improving the operational efficiency of ports has become an important issue in containership operations. Arrangement of containers both within the container terminal and on the containership play an important role in determining the berthing time. The berthing time of a containership is mainly composed of the unloading and loading time of containers. Containers in a containership are stored in stacks, making a container directly accessible only if it is on the top of one stack. The task of determining a good container arrangement to minimize the number of re-handlings while maintaining the ship's stability over several ports is called stowage planning, which is an everyday problem solved by ship planners. The horizontal distribution of the containers over the bays affects crane utilization and overall ship berthing time. In order to increase the terminal productivity and reduce the turnaround time, the stowage planning must conform to the berth design. Given the configuration of berths and cranes at each visiting port, the stowage planning must take into account the utilization of quay cranes as well as the reduction of unnecessary shifts to minimize the total time at all ports over the voyage. This dissertation introduces an optimization model to solve the stowage planning problem with crane utilization considerations. The optimization model covers a wide range of operational and structural constraints for containership load planning. In order to solve real-size problems, a meta-heuristic approach based on genetic algorithms is designed and implemented which embeds a crane split approximation routine. The genetic encoding is ultra-compact and represents grouping, sorting and assignment strategies that might be applied to form the stowage pattern. The evaluation procedure accounts for technical specification of the cranes as well as the crane split. Numerical results show that timely solution for ultra large size containerships can be obtained under different scenarios.en_US
dc.identifier.urihttp://hdl.handle.net/1903/11562
dc.subject.pqcontrolledTransportationen_US
dc.subject.pqcontrolledOperations Researchen_US
dc.subject.pquncontrolledContaineren_US
dc.subject.pquncontrolledContainershipen_US
dc.subject.pquncontrolledCraneen_US
dc.subject.pquncontrolledMarineen_US
dc.subject.pquncontrolledStowageen_US
dc.subject.pquncontrolledTerminalen_US
dc.titleContainership Load Planning with Crane Operationsen_US
dc.typeDissertationen_US

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