Hierarchical Facility Location Model for allocating cancer treatment units in interior of Rio de Janeiro

Detalhes bibliográficos
Autor(a) principal: Vieira,Isabella Fischer Guindani
Data de Publicação: 2019
Outros Autores: Barros,Matheus Ferreira de, Cormack,Allan
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Production
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-65132019000100804
Resumo: Abstract Paper aims This work aims at proposing a mathematical model for allocation of oncological treatment units of SUS. Originality A model of the same architecture was not found in the literature for the delimited problem. Research method The mathematical models of location in the literature were reviewed and based the choice by the two-level hierarchical pq-median model with additional constraints of maximum distance and vertices eligibility, which was implemented in the CPLEX optimization software. Main findings Satisfactory results with homogeneous networks, centralized facilities in their service area and shorter distance traveled by users indicate the efficiency of the model in determining the optimum location given the number of facilities to be allocated. Implications for theory and practice The model proved to be an efficient tool to assist health managers in their decision-making about the network of facilities, not just oncological, but of any nature and many others public sectors.
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spelling Hierarchical Facility Location Model for allocating cancer treatment units in interior of Rio de JaneiroFacility location problemsInteger programmingOncologyAbstract Paper aims This work aims at proposing a mathematical model for allocation of oncological treatment units of SUS. Originality A model of the same architecture was not found in the literature for the delimited problem. Research method The mathematical models of location in the literature were reviewed and based the choice by the two-level hierarchical pq-median model with additional constraints of maximum distance and vertices eligibility, which was implemented in the CPLEX optimization software. Main findings Satisfactory results with homogeneous networks, centralized facilities in their service area and shorter distance traveled by users indicate the efficiency of the model in determining the optimum location given the number of facilities to be allocated. Implications for theory and practice The model proved to be an efficient tool to assist health managers in their decision-making about the network of facilities, not just oncological, but of any nature and many others public sectors.Associação Brasileira de Engenharia de Produção2019-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-65132019000100804Production v.29 2019reponame:Productioninstname:Associação Brasileira de Engenharia de Produção (ABEPRO)instacron:ABEPRO10.1590/0103-6513.20190026info:eu-repo/semantics/openAccessVieira,Isabella Fischer GuindaniBarros,Matheus Ferreira deCormack,Allaneng2019-10-29T00:00:00Zoai:scielo:S0103-65132019000100804Revistahttps://www.scielo.br/j/prod/https://old.scielo.br/oai/scielo-oai.php||production@editoracubo.com.br1980-54110103-6513opendoar:2019-10-29T00:00Production - Associação Brasileira de Engenharia de Produção (ABEPRO)false
dc.title.none.fl_str_mv Hierarchical Facility Location Model for allocating cancer treatment units in interior of Rio de Janeiro
title Hierarchical Facility Location Model for allocating cancer treatment units in interior of Rio de Janeiro
spellingShingle Hierarchical Facility Location Model for allocating cancer treatment units in interior of Rio de Janeiro
Vieira,Isabella Fischer Guindani
Facility location problems
Integer programming
Oncology
title_short Hierarchical Facility Location Model for allocating cancer treatment units in interior of Rio de Janeiro
title_full Hierarchical Facility Location Model for allocating cancer treatment units in interior of Rio de Janeiro
title_fullStr Hierarchical Facility Location Model for allocating cancer treatment units in interior of Rio de Janeiro
title_full_unstemmed Hierarchical Facility Location Model for allocating cancer treatment units in interior of Rio de Janeiro
title_sort Hierarchical Facility Location Model for allocating cancer treatment units in interior of Rio de Janeiro
author Vieira,Isabella Fischer Guindani
author_facet Vieira,Isabella Fischer Guindani
Barros,Matheus Ferreira de
Cormack,Allan
author_role author
author2 Barros,Matheus Ferreira de
Cormack,Allan
author2_role author
author
dc.contributor.author.fl_str_mv Vieira,Isabella Fischer Guindani
Barros,Matheus Ferreira de
Cormack,Allan
dc.subject.por.fl_str_mv Facility location problems
Integer programming
Oncology
topic Facility location problems
Integer programming
Oncology
description Abstract Paper aims This work aims at proposing a mathematical model for allocation of oncological treatment units of SUS. Originality A model of the same architecture was not found in the literature for the delimited problem. Research method The mathematical models of location in the literature were reviewed and based the choice by the two-level hierarchical pq-median model with additional constraints of maximum distance and vertices eligibility, which was implemented in the CPLEX optimization software. Main findings Satisfactory results with homogeneous networks, centralized facilities in their service area and shorter distance traveled by users indicate the efficiency of the model in determining the optimum location given the number of facilities to be allocated. Implications for theory and practice The model proved to be an efficient tool to assist health managers in their decision-making about the network of facilities, not just oncological, but of any nature and many others public sectors.
publishDate 2019
dc.date.none.fl_str_mv 2019-01-01
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dc.publisher.none.fl_str_mv Associação Brasileira de Engenharia de Produção
publisher.none.fl_str_mv Associação Brasileira de Engenharia de Produção
dc.source.none.fl_str_mv Production v.29 2019
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