Using Analytics to Enhance a Food Retailer's Shelf-Space Management

dc.contributor.author Bianchi Aguiar,T en
dc.contributor.author Elsa Marília Silva en
dc.contributor.author Luís Guimarães en
dc.contributor.author Maria Antónia Carravilla en
dc.contributor.author José Fernando Oliveira en
dc.contributor.author Amaral,JG en
dc.contributor.author Liz,J en
dc.contributor.author Lapela,S en
dc.date.accessioned 2018-01-08T09:52:18Z
dc.date.available 2018-01-08T09:52:18Z
dc.date.issued 2016 en
dc.description.abstract This paper describes the results of our collaboration with the leading Portuguese food retailer to address the shelf-space planning problem of allocating products to shop-floor shelves. Our challenge was to introduce analytical methods into the shelf-space planning process to improve the return on space and automate a process heavily dependent on the experience of the retailer's space managers. This led to the creation of GAP, a decision support system that the company's space-management team uses daily. We developed a modular operations research approach that systematically applies mathematical programming models and heuristics to determine the best layout of products on the shelves. GAP combines its analytical strength with an ability to incorporate different types of merchandising rules to balance the tradeoff between optimization and customization. en
dc.identifier.uri http://repositorio.inesctec.pt/handle/123456789/5702
dc.identifier.uri http://dx.doi.org/10.1287/inte.2016.0859 en
dc.language eng en
dc.relation 5965 en
dc.relation 1297 en
dc.relation 265 en
dc.relation 5675 en
dc.rights info:eu-repo/semantics/embargoedAccess en
dc.title Using Analytics to Enhance a Food Retailer's Shelf-Space Management en
dc.type article en
dc.type Publication en
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