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Order batching in warehouses by minimizing total tardiness: a hybrid approach of weighted association rule mining and genetic algorithms

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dc.contributor.author Hossein Azadnia, Amir
dc.contributor.author Taheri, Shahrooz
dc.contributor.author Ghadimi, Pezhman
dc.contributor.author Zameri Mat Saman, Muhamad
dc.contributor.author Yew Wong, Kuan
dc.date.accessioned 2017-10-19T13:43:19Z
dc.date.available 2017-10-19T13:43:19Z
dc.date.issued 2013
dc.identifier.uri http://hdl.handle.net/10344/6182
dc.description peer-reviewed en_US
dc.description.abstract One of the cost-intensive issues in managing warehouses is the order picking problem which deals with the retrieval of items from their storage locations in order to meet customer requests. Many solution approaches have been proposed in order to minimize traveling distance in the process of order picking. However, in practice, customer orders have to be completed by certain due dates in order to avoid tardiness which is neglected in most of the related scientific papers. Consequently, we proposed a novel solution approach in order to minimize tardinesswhich consists of four phases. First of all,weighted association rule mining has been used to calculate associations between orders with respect to their due date. Next, a batching model based on binary integer programming has been formulated to maximize the associations between orders within each batch. Subsequently, the order picking phase will come up which used a Genetic Algorithm integrated with the Traveling Salesman Problem in order to identify the most suitable travel path. Finally, the Genetic Algorithm has been applied for sequencing the constructed batches in order to minimize tardiness. Illustrative examples and comparisons are presented to demonstrate the proficiency and solution quality of the proposed approach en_US
dc.language.iso eng en_US
dc.publisher Hindawi Publishing Corporation en_US
dc.relation.ispartofseries The ScientificWorld Journal;246578, 13 pages
dc.subject order batching en_US
dc.subject warehouses en_US
dc.subject minimizing en_US
dc.subject total tardiness en_US
dc.subject hybrid approach en_US
dc.subject weighted en_US
dc.subject association rule mining en_US
dc.subject genetic algorithms en_US
dc.title Order batching in warehouses by minimizing total tardiness: a hybrid approach of weighted association rule mining and genetic algorithms en_US
dc.type info:eu-repo/semantics/article en_US
dc.type.supercollection all_ul_research en_US
dc.type.supercollection ul_published_reviewed en_US
dc.identifier.doi 10.1155/2013/246578
dc.rights.accessrights info:eu-repo/semantics/openAccess en_US


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