Allocating products on shelves under merchandising rules: Multi-level product families with display directions

Detalhes bibliográficos
Autor(a) principal: Teresa Bianchi Aguiar
Data de Publicação: 2018
Outros Autores: Elsa Marília Silva, Luís Guimarães, Maria Antónia Carravilla, José Fernando Oliveira
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://repositorio.inesctec.pt/handle/123456789/6332
http://dx.doi.org/10.1016/j.omega.2017.04.002
Resumo: Retailers’ individual products are categorized as part of product families. Merchandising rules specify how the products should be arranged on the shelves using product families, creating more structured displays capable of increasing the viewers’ attention. This paper presents a novel mixed integer programming formulation for the Shelf Space Allocation Problem considering two innovative features emerging from merchandising rules: hierarchical product families and display directions. The formulation uses single commodity flow constraints to model product sequencing and explores the product families’ hierarchy to reduce the combinatorial nature of the problem. Based on the formulation, a mathematical programming-based heuristic was also developed that uses product families to decompose the problem into a sequence of sub-problems. To improve performance, its original design was adapted following two directions: recovery from infeasible solutions and reduction of solution times. A new set of real case benchmark instances is also provided, which was used to assess the formulation and the matheuristic. This approach will allow retailers to efficiently create planograms capable of following merchandising rules and optimizing shelf space revenue. © 2017 Elsevier Ltd
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spelling Allocating products on shelves under merchandising rules: Multi-level product families with display directionsRetailers’ individual products are categorized as part of product families. Merchandising rules specify how the products should be arranged on the shelves using product families, creating more structured displays capable of increasing the viewers’ attention. This paper presents a novel mixed integer programming formulation for the Shelf Space Allocation Problem considering two innovative features emerging from merchandising rules: hierarchical product families and display directions. The formulation uses single commodity flow constraints to model product sequencing and explores the product families’ hierarchy to reduce the combinatorial nature of the problem. Based on the formulation, a mathematical programming-based heuristic was also developed that uses product families to decompose the problem into a sequence of sub-problems. To improve performance, its original design was adapted following two directions: recovery from infeasible solutions and reduction of solution times. A new set of real case benchmark instances is also provided, which was used to assess the formulation and the matheuristic. This approach will allow retailers to efficiently create planograms capable of following merchandising rules and optimizing shelf space revenue. © 2017 Elsevier Ltd2018-01-16T12:11:10Z2018-01-01T00:00:00Z2018info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://repositorio.inesctec.pt/handle/123456789/6332http://dx.doi.org/10.1016/j.omega.2017.04.002engTeresa Bianchi AguiarElsa Marília SilvaLuís GuimarãesMaria Antónia CarravillaJosé Fernando Oliveirainfo:eu-repo/semantics/embargoedAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-05-15T10:19:55Zoai:repositorio.inesctec.pt:123456789/6332Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:52:25.614256Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Allocating products on shelves under merchandising rules: Multi-level product families with display directions
title Allocating products on shelves under merchandising rules: Multi-level product families with display directions
spellingShingle Allocating products on shelves under merchandising rules: Multi-level product families with display directions
Teresa Bianchi Aguiar
title_short Allocating products on shelves under merchandising rules: Multi-level product families with display directions
title_full Allocating products on shelves under merchandising rules: Multi-level product families with display directions
title_fullStr Allocating products on shelves under merchandising rules: Multi-level product families with display directions
title_full_unstemmed Allocating products on shelves under merchandising rules: Multi-level product families with display directions
title_sort Allocating products on shelves under merchandising rules: Multi-level product families with display directions
author Teresa Bianchi Aguiar
author_facet Teresa Bianchi Aguiar
Elsa Marília Silva
Luís Guimarães
Maria Antónia Carravilla
José Fernando Oliveira
author_role author
author2 Elsa Marília Silva
Luís Guimarães
Maria Antónia Carravilla
José Fernando Oliveira
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Teresa Bianchi Aguiar
Elsa Marília Silva
Luís Guimarães
Maria Antónia Carravilla
José Fernando Oliveira
description Retailers’ individual products are categorized as part of product families. Merchandising rules specify how the products should be arranged on the shelves using product families, creating more structured displays capable of increasing the viewers’ attention. This paper presents a novel mixed integer programming formulation for the Shelf Space Allocation Problem considering two innovative features emerging from merchandising rules: hierarchical product families and display directions. The formulation uses single commodity flow constraints to model product sequencing and explores the product families’ hierarchy to reduce the combinatorial nature of the problem. Based on the formulation, a mathematical programming-based heuristic was also developed that uses product families to decompose the problem into a sequence of sub-problems. To improve performance, its original design was adapted following two directions: recovery from infeasible solutions and reduction of solution times. A new set of real case benchmark instances is also provided, which was used to assess the formulation and the matheuristic. This approach will allow retailers to efficiently create planograms capable of following merchandising rules and optimizing shelf space revenue. © 2017 Elsevier Ltd
publishDate 2018
dc.date.none.fl_str_mv 2018-01-16T12:11:10Z
2018-01-01T00:00:00Z
2018
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http://dx.doi.org/10.1016/j.omega.2017.04.002
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http://dx.doi.org/10.1016/j.omega.2017.04.002
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