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dc.contributor.advisorJimenez, Jesus A.
dc.contributor.advisorPerez, Eduardo A.
dc.contributor.authorLi, Yue ( )
dc.date.accessioned2017-08-25T13:37:40Z
dc.date.available2017-08-25T13:37:40Z
dc.date.created2017-08
dc.date.issued2017-08
dc.identifier.citationLi, Y. (2017). A data-intensive analysis augmented simulation model of an order picking operation (Unpublished thesis). Texas State University, San Marcos, Texas.
dc.identifier.urihttps://digital.library.txstate.edu/handle/10877/6774
dc.description.abstractOrder picking is the most labor-intensive function of distribution centers (DC) in the food and beverage store industry. An efficient order picking process supports this industry’s supply chain to move high volumes of products between the DC and the retail stores. This thesis focuses on the storage location assignment problem to deciding via an algorithm based on Association Rules Mining (ARM) the most adequate location of incoming products. The algorithm analyzes hundreds of orders received by the DC to find correlated products that are ordered frequently together by retail stores. The algorithm then assigns correlated products to storage locations that are close to each other in order to minimize order picking times. The results of computer simulation experiments using data from a real distribution center will be presented to evaluate the performance of the DC layout resulting from ARM.
dc.formatText
dc.format.extent108 pages
dc.format.medium1 file (.pdf)
dc.language.isoen
dc.subjectSimulation
dc.subjectData-intensive analysis
dc.subjectDistribution center
dc.subjectFacilities layout
dc.subjectOrder picking
dc.subjectAssociation rules
dc.subject.lcshData miningen_US
dc.subject.lcshInformation storage and retrieval systemsen_US
dc.subject.lcshBusiness--Data processingen_US
dc.titleA data-intensive analysis augmented simulation model of an order picking operation
txstate.documenttypeThesis
dc.contributor.committeeMemberMéndez Mediavilla, Francis
thesis.degree.departmentEngineering Technology
thesis.degree.disciplineEngineering
thesis.degree.grantorTexas State University
thesis.degree.levelMasters
thesis.degree.nameMaster of Science
dc.description.departmentEngineering Technology


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