Please use this identifier to cite or link to this item: http://repositorio.inesctec.pt/handle/123456789/5702
Title: Using Analytics to Enhance a Food Retailer's Shelf-Space Management
Authors: Bianchi Aguiar,T
Elsa Marília Silva
Luís Guimarães
Maria Antónia Carravilla
José Fernando Oliveira
Amaral,JG
Liz,J
Lapela,S
Issue Date: 2016
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.
URI: http://repositorio.inesctec.pt/handle/123456789/5702
http://dx.doi.org/10.1287/inte.2016.0859
metadata.dc.type: article
Publication
Appears in Collections:CEGI - Articles in International Journals

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