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Improving picking performance at a large retailer warehouse by combining probabilistic simulation, optimization, and discreteā€event simulation

2021Journal article Restricted access
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dc.contributor.authorAmorim-Lopes, MƔrio
dc.contributor.authorGuimarĆ£es, LuĆ­s
dc.contributor.authorAlves, JoĆ£o
dc.contributor.authorAlmada-Lobo, Bernardo
dc.date.accessioned2020-09-22T09:14:04Z
dc.date.available2020-09-22T09:14:04Z
dc.date.issued2021
dc.description.abstractDistribution warehouses are a critical part of supply chains, representing a nonnegligible share of the operating costs. This is especially true for unautomated, laborā€intensive warehouses, partially due to timeā€consuming activities such as picking up items or traveling. Inventory categorization techniques, as well as zone storage assignment policies, may help in improving operations, but may also be shortā€sighted. This work presents a threeā€step methodology that uses probabilistic simulation, optimization, and eventā€based simulation (SOS) to analyze and experiment with layout and storage assignment policies to improve the picking performance. In the first stage, picking performance is estimated under different storage assignment policies and zone configurations using a probabilistic model. In the second stage, a mixed integer optimization model defines the overall warehouse layout by selecting the configuration and storage assignment policy for each zone. Finally, the optimized layout solution is tested under demand uncertainty in the third, final simulation phase, through a discreteā€event simulation model. The SOS methodology was validated with three months of operational data from a large retailer's warehouse, successfully illustrating how it may be successfully used for improving the performance of a distribution warehouse.pt_PT
dc.description.versionN/Apt_PT
dc.identifier.citationAmorimā€Lopes, M., GuimarĆ£es, L., Alves, J., Almadaā€Lobo, B. (2020). Improving picking performance at a large retailer warehouse by combining probabilistic simulation, optimization, and discreteā€event simulation. International Transactions in Operational Researchpt_PT
dc.identifier.doi10.1111/itor.12852pt_PT
dc.identifier.eid85088780800
dc.identifier.eissn1475-3995
dc.identifier.issn0969-6016
dc.identifier.urihttp://hdl.handle.net/10400.14/30935
dc.identifier.wos000555647700001
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherWileypt_PT
dc.subjectWarehouse designpt_PT
dc.subjectStorage assignment policiespt_PT
dc.subjectPicking performancept_PT
dc.subjectDiscrete-event simulationpt_PT
dc.subjectMixed integer programmingpt_PT
dc.subjectSimulation-optimizationpt_PT
dc.titleImproving picking performance at a large retailer warehouse by combining probabilistic simulation, optimization, and discreteā€event simulationpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage715
oaire.citation.issue1
oaire.citation.startPage687
oaire.citation.titleInternational Transactions in Operational Researchpt_PT
oaire.citation.volume28
person.familyNameAmorim Lopes
person.familyNameBarbosa GuimarĆ£es
person.familyNameAlmada-Lobo
person.givenNameMƔrio
person.givenNameLuĆ­s Alexandre
person.givenNameBernardo
person.identifier.ciencia-idF610-57AD-B20F
person.identifier.ciencia-id621B-3AEB-1FF4
person.identifier.ciencia-idB31A-1959-E5E1
person.identifier.orcid0000-0001-9609-4723
person.identifier.orcid0000-0001-7101-4264
person.identifier.orcid0000-0003-0815-1068
person.identifier.scopus-author-id20733263600
rcaap.rightsrestrictedAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublicationb3f4ff08-62d2-4923-b616-32811da17b79
relation.isAuthorOfPublication7ade72be-934a-4bee-8d09-052ccbdfb20c
relation.isAuthorOfPublication03cdba84-7645-4676-8aaa-eac61abd3b6b
relation.isAuthorOfPublication.latestForDiscovery7ade72be-934a-4bee-8d09-052ccbdfb20c

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