RESTAURANT RESERVATION MANAGEMENT CONSIDERING TABLE COMBINATION

Detalhes bibliográficos
Autor(a) principal: Miao,Qing
Data de Publicação: 2018
Outros Autores: Li,Yihua, Wang,Xiubin B.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Pesquisa operacional (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382018000100073
Resumo: ABSTRACT This paper presents a case study of table reservation practice for restaurant business within Walt Disney World. A unique feature here is to consider table combination to capture revenue potentials from different party sizes and at different time periods. For example, a party of large size can be served by combining two or more small tables. A mixed integer programming (MIP) model is developed to make the reservation recommendation. We propose a rolling horizon reservation policy such that the value of a particular table is periodically evaluated and updated. This is a typical revenue management method in the airlines and other industries, the essence of which is to compare the future expected revenue with a currently offered price. Using historical data, numerical test shows a significant revenue improvement potential from our proposed model.
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spelling RESTAURANT RESERVATION MANAGEMENT CONSIDERING TABLE COMBINATIONRestaurant Revenue ManagementTable Reservation OptimizationLinear ProgrammingABSTRACT This paper presents a case study of table reservation practice for restaurant business within Walt Disney World. A unique feature here is to consider table combination to capture revenue potentials from different party sizes and at different time periods. For example, a party of large size can be served by combining two or more small tables. A mixed integer programming (MIP) model is developed to make the reservation recommendation. We propose a rolling horizon reservation policy such that the value of a particular table is periodically evaluated and updated. This is a typical revenue management method in the airlines and other industries, the essence of which is to compare the future expected revenue with a currently offered price. Using historical data, numerical test shows a significant revenue improvement potential from our proposed model.Sociedade Brasileira de Pesquisa Operacional2018-04-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382018000100073Pesquisa Operacional v.38 n.1 2018reponame:Pesquisa operacional (Online)instname:Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)instacron:SOBRAPO10.1590/0101-7438.2018.038.01.0073info:eu-repo/semantics/openAccessMiao,QingLi,YihuaWang,Xiubin B.eng2018-04-13T00:00:00Zoai:scielo:S0101-74382018000100073Revistahttp://www.scielo.br/popehttps://old.scielo.br/oai/scielo-oai.php||sobrapo@sobrapo.org.br1678-51420101-7438opendoar:2018-04-13T00:00Pesquisa operacional (Online) - Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)false
dc.title.none.fl_str_mv RESTAURANT RESERVATION MANAGEMENT CONSIDERING TABLE COMBINATION
title RESTAURANT RESERVATION MANAGEMENT CONSIDERING TABLE COMBINATION
spellingShingle RESTAURANT RESERVATION MANAGEMENT CONSIDERING TABLE COMBINATION
Miao,Qing
Restaurant Revenue Management
Table Reservation Optimization
Linear Programming
title_short RESTAURANT RESERVATION MANAGEMENT CONSIDERING TABLE COMBINATION
title_full RESTAURANT RESERVATION MANAGEMENT CONSIDERING TABLE COMBINATION
title_fullStr RESTAURANT RESERVATION MANAGEMENT CONSIDERING TABLE COMBINATION
title_full_unstemmed RESTAURANT RESERVATION MANAGEMENT CONSIDERING TABLE COMBINATION
title_sort RESTAURANT RESERVATION MANAGEMENT CONSIDERING TABLE COMBINATION
author Miao,Qing
author_facet Miao,Qing
Li,Yihua
Wang,Xiubin B.
author_role author
author2 Li,Yihua
Wang,Xiubin B.
author2_role author
author
dc.contributor.author.fl_str_mv Miao,Qing
Li,Yihua
Wang,Xiubin B.
dc.subject.por.fl_str_mv Restaurant Revenue Management
Table Reservation Optimization
Linear Programming
topic Restaurant Revenue Management
Table Reservation Optimization
Linear Programming
description ABSTRACT This paper presents a case study of table reservation practice for restaurant business within Walt Disney World. A unique feature here is to consider table combination to capture revenue potentials from different party sizes and at different time periods. For example, a party of large size can be served by combining two or more small tables. A mixed integer programming (MIP) model is developed to make the reservation recommendation. We propose a rolling horizon reservation policy such that the value of a particular table is periodically evaluated and updated. This is a typical revenue management method in the airlines and other industries, the essence of which is to compare the future expected revenue with a currently offered price. Using historical data, numerical test shows a significant revenue improvement potential from our proposed model.
publishDate 2018
dc.date.none.fl_str_mv 2018-04-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382018000100073
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382018000100073
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0101-7438.2018.038.01.0073
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Sociedade Brasileira de Pesquisa Operacional
publisher.none.fl_str_mv Sociedade Brasileira de Pesquisa Operacional
dc.source.none.fl_str_mv Pesquisa Operacional v.38 n.1 2018
reponame:Pesquisa operacional (Online)
instname:Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)
instacron:SOBRAPO
instname_str Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)
instacron_str SOBRAPO
institution SOBRAPO
reponame_str Pesquisa operacional (Online)
collection Pesquisa operacional (Online)
repository.name.fl_str_mv Pesquisa operacional (Online) - Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)
repository.mail.fl_str_mv ||sobrapo@sobrapo.org.br
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