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dc.contributor.authorRoy, Debjit
dc.contributor.authorKrishnamurthy, Ananth
dc.contributor.authorHeragu, Sunderesh
dc.contributor.authorMalmborg, Charles
dc.date.accessioned2017-06-07T12:00:49Z
dc.date.available2017-06-07T12:00:49Z
dc.date.issued2015
dc.identifier.urihttp://hdl.handle.net/11718/19359
dc.description.abstractTechnological innovations in warehouse automation systems, such as Autonomous Vehicle based Storage and Retrieval System (AVS/RS), are geared towards achieving greater operational efficiency and flexibility that would be necessary in warehouses of the future. AVS/RS relies on autonomous vehicles and lifts for horizontal and vertical transfer of unit-loads respectively. To implement a new technology such as AVS/RS, the choice of a design variable setting, interactions among the design variables, and the design trade-offs need to be well understood. In particular, design decisions such as the choice of vehicle dwell-point and location of cross-aisles could significantly affect the performance of an AVS/RS. Hence, we investigate the effect of these design decisions using customized analytical models based on multi-class semi-open queuing network theory. Numerical studies suggest that the average percentage reduction in storage and retrieval transactions with appropriate choice of dwell-point is about 8 percent and 4 percent respectively. While end of aisle location of the cross-aisle is commonly used in practice, our model suggests that there exists a better cross-aisle location within a tier (about 15 percent from end of aisle); however, the cycle time benefits by choosing the optimal cross-aisle location in comparison to the end of aisle cross-aisle location is marginal. Detailed simulations also indicate that the analytical model yields fairly accurate results.en_US
dc.language.isoen_USen_US
dc.publisherEuropean Journal of Operational Researchen_US
dc.subjectFacilities planning and designen_US
dc.subjectLogisticsen_US
dc.subjectQueuingen_US
dc.subjectSimulationen_US
dc.titleQueuing models to analyze dwell-point and cross-aisle location in autonomous vehicle-based warehouse systemsen_US
dc.typeArticleen_US


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