WarehouseVis: A Visual Analytics Approach to Facilitating Warehouse Location Selection for Business Districts

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dc.contributor.authorLi, Quanen_US
dc.contributor.authorLiu, Qiangqiangen_US
dc.contributor.authorTang, Chunfengen_US
dc.contributor.authorLi, Zhiweien_US
dc.contributor.authorWei, Shuaichaoen_US
dc.contributor.authorPeng, Xianruien_US
dc.contributor.authorZheng, Minghuaen_US
dc.contributor.authorChen, Tianjianen_US
dc.contributor.authorYang, Qiangen_US
dc.contributor.editorViola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatianaen_US
dc.date.accessioned2020-05-24T13:01:41Z
dc.date.available2020-05-24T13:01:41Z
dc.date.issued2020
dc.description.abstractSelecting a proper warehouse location serving to satisfy the demands of the goods from a certain business area is important to a successful retail business. However, the large solution space, uncertain traffic conditions, and varying business preferences impose great challenges on warehouse location selection. Conventional approaches mainly summarize relevant evaluation criteria and compile them into an analysis report to facilitate rapid data absorption but fail to support a comprehensive and joint decision-making process in warehouse location selection. In this paper, we propose a visual analytics approach to facilitating warehouse location selection. We first visually centralize relevant information of warehouses and adapts a widely-used methodology to efficiently rank warehouse candidates. We then design a delivering estimation model based on massive logistics trajectories to resolve the uncertainty issue of traffic conditions of warehouses. Based on these techniques, an interactive framework is proposed to generate and explore the candidate warehouses. We conduct a case study and a within-subject study with baseline systems to assess the efficacy of our system. Experts' feedback also suggests that our approach indeed helps them better tackle the problem of finding an ideal warehouse in the field of retail logistics management.en_US
dc.description.number3
dc.description.sectionheadersVisual Analytics for Problem Solving
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume39
dc.identifier.doi10.1111/cgf.13996
dc.identifier.issn1467-8659
dc.identifier.pages483-495
dc.identifier.urihttps://doi.org/10.1111/cgf.13996
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf13996
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/]
dc.subjectHuman centered computing
dc.subjectVisualization
dc.subjectVisualization design and evaluation methods
dc.titleWarehouseVis: A Visual Analytics Approach to Facilitating Warehouse Location Selection for Business Districtsen_US
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