A genetic algorithm approach for the TV self-promotion assignment problem

Detalhes bibliográficos
Autor(a) principal: Pereira, P. A.
Data de Publicação: 2009
Outros Autores: Fontes, Fernando A. C. C., Fontes, Dalila B. M. M.
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/1822/11805
Resumo: We report on the development of a Genetic Algorithm (GA), which has been integrated into a Decision Support System to plan the best assignment of the weekly self-promotion space for a TV station. The problem addressed consists on deciding which shows to advertise and when such that the number of viewers, of an intended group or target, is maximized. The GA proposed incorporates a greedy heuristic to find good initial solutions. These solutions, as well as the solutions later obtained through the use of the GA, go then through a repair procedure. This is used with two objectives, which are addressed in turn. Firstly, it checks the solution feasibility and if unfeasible it is fixed by removing some shows. Secondly, it tries to improve the solution by adding some extra shows. Since the problem faced by the commercial TV station is too big and has too many features it cannot be solved exactly. Therefore, in order to test the quality of the solutions provided by the proposed GA we have randomly generated some smaller problem instances. For these problems we have obtained solutions on average within 1% of the optimal solution value.
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spelling A genetic algorithm approach for the TV self-promotion assignment problemGenetic AlgorithmsCombinatorial optimizationImage processingNumerical optimizationTV self-promotionAssignment problemTV Self-Promotion Assignment ProblemScience & TechnologyWe report on the development of a Genetic Algorithm (GA), which has been integrated into a Decision Support System to plan the best assignment of the weekly self-promotion space for a TV station. The problem addressed consists on deciding which shows to advertise and when such that the number of viewers, of an intended group or target, is maximized. The GA proposed incorporates a greedy heuristic to find good initial solutions. These solutions, as well as the solutions later obtained through the use of the GA, go then through a repair procedure. This is used with two objectives, which are addressed in turn. Firstly, it checks the solution feasibility and if unfeasible it is fixed by removing some shows. Secondly, it tries to improve the solution by adding some extra shows. Since the problem faced by the commercial TV station is too big and has too many features it cannot be solved exactly. Therefore, in order to test the quality of the solutions provided by the proposed GA we have randomly generated some smaller problem instances. For these problems we have obtained solutions on average within 1% of the optimal solution value.AIP PublishingUniversidade do MinhoPereira, P. A.Fontes, Fernando A. C. C.Fontes, Dalila B. M. M.20092009-01-01T00:00:00Zconference paperinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/1822/11805engSIMOS, Theodore E. ; PSIHOYIOS, George ; TSITOURAS, Ch., eds – “Numerical Analysis and Applied Mathematics : International Conference on Numerical Analysis and Applied Mathematics, Rethymno, Crete (Greece), 2009.” Melville : American Institute of Physics, 2009. ISBN 978-0-7354-0709. vol. 2, p. 1378-1381.978-0-7354-07090094-243X10.1063/1.3241343http://scitation.aip.org/getabs/servlet/GetabsServlet?prog=normal&id=APCPCS001168000001001378000001&idtype=cvips&gifs=yes&ref=noinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-05-11T06:08:58Zoai:repositorium.sdum.uminho.pt:1822/11805Portal AgregadorONGhttps://www.rcaap.pt/oai/openairemluisa.alvim@gmail.comopendoar:71602024-05-11T06:08:58Repositório 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 A genetic algorithm approach for the TV self-promotion assignment problem
title A genetic algorithm approach for the TV self-promotion assignment problem
spellingShingle A genetic algorithm approach for the TV self-promotion assignment problem
Pereira, P. A.
Genetic Algorithms
Combinatorial optimization
Image processing
Numerical optimization
TV self-promotion
Assignment problem
TV Self-Promotion Assignment Problem
Science & Technology
title_short A genetic algorithm approach for the TV self-promotion assignment problem
title_full A genetic algorithm approach for the TV self-promotion assignment problem
title_fullStr A genetic algorithm approach for the TV self-promotion assignment problem
title_full_unstemmed A genetic algorithm approach for the TV self-promotion assignment problem
title_sort A genetic algorithm approach for the TV self-promotion assignment problem
author Pereira, P. A.
author_facet Pereira, P. A.
Fontes, Fernando A. C. C.
Fontes, Dalila B. M. M.
author_role author
author2 Fontes, Fernando A. C. C.
Fontes, Dalila B. M. M.
author2_role author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Pereira, P. A.
Fontes, Fernando A. C. C.
Fontes, Dalila B. M. M.
dc.subject.por.fl_str_mv Genetic Algorithms
Combinatorial optimization
Image processing
Numerical optimization
TV self-promotion
Assignment problem
TV Self-Promotion Assignment Problem
Science & Technology
topic Genetic Algorithms
Combinatorial optimization
Image processing
Numerical optimization
TV self-promotion
Assignment problem
TV Self-Promotion Assignment Problem
Science & Technology
description We report on the development of a Genetic Algorithm (GA), which has been integrated into a Decision Support System to plan the best assignment of the weekly self-promotion space for a TV station. The problem addressed consists on deciding which shows to advertise and when such that the number of viewers, of an intended group or target, is maximized. The GA proposed incorporates a greedy heuristic to find good initial solutions. These solutions, as well as the solutions later obtained through the use of the GA, go then through a repair procedure. This is used with two objectives, which are addressed in turn. Firstly, it checks the solution feasibility and if unfeasible it is fixed by removing some shows. Secondly, it tries to improve the solution by adding some extra shows. Since the problem faced by the commercial TV station is too big and has too many features it cannot be solved exactly. Therefore, in order to test the quality of the solutions provided by the proposed GA we have randomly generated some smaller problem instances. For these problems we have obtained solutions on average within 1% of the optimal solution value.
publishDate 2009
dc.date.none.fl_str_mv 2009
2009-01-01T00:00:00Z
dc.type.driver.fl_str_mv conference paper
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/1822/11805
url http://hdl.handle.net/1822/11805
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv SIMOS, Theodore E. ; PSIHOYIOS, George ; TSITOURAS, Ch., eds – “Numerical Analysis and Applied Mathematics : International Conference on Numerical Analysis and Applied Mathematics, Rethymno, Crete (Greece), 2009.” Melville : American Institute of Physics, 2009. ISBN 978-0-7354-0709. vol. 2, p. 1378-1381.
978-0-7354-0709
0094-243X
10.1063/1.3241343
http://scitation.aip.org/getabs/servlet/GetabsServlet?prog=normal&id=APCPCS001168000001001378000001&idtype=cvips&gifs=yes&ref=no
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv AIP Publishing
publisher.none.fl_str_mv AIP Publishing
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv mluisa.alvim@gmail.com
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